Adaptive parameter selection for cross-component prediction in image and video compression

ABSTRACT

Aspects of the disclosure provide a method and an apparatus including processing circuitry that decodes prediction information indicating a cross-component linear model (CCLM) mode being applied to a chroma block in a current picture. For a first region in the chroma block, the processing circuitry determines a first adjustment value used to modify an offset parameter in the CCLM mode based on a first subset of reconstructed samples in a luma block collocated with the chroma block. The first subset of the reconstructed samples does not include one or more samples in the luma block. The processing circuitry updates the offset parameter based on the first adjustment value. The processing circuitry determines a second adjustment value used to modify a slope parameter in the CCLM mode based on a second subset of the reconstructed samples in the luma block and updates the slope parameter based on the second adjustment value.

INCORPORATION BY REFERENCE

The present application claims the benefit of priority to U.S.Provisional Application No. 63/305,159, “ADAPTIVE PARAMETER SELECTIONFOR CROSS-COMPONENT PREDICTION IN IMAGE AND VIDEO COMPRESSION” filed onJan. 31, 2022, which is incorporated by reference herein in itsentirety.

TECHNICAL FIELD

The present disclosure describes embodiments generally related to videocoding.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Uncompressed digital images and/or video can include a series ofpictures, each picture having a spatial dimension of, for example,1920×1080 luminance samples and associated chrominance samples. Theseries of pictures can have a fixed or variable picture rate (informallyalso known as frame rate), of, for example 60 pictures per second or 60Hz. Uncompressed image and/or video has specific bitrate requirements.For example, 1080p60 4:2:0 video at 8 bit per sample (1920×1080luminance sample resolution at 60 Hz frame rate) requires close to 1.5Gbit/s bandwidth. An hour of such video requires more than 600 GBytes ofstorage space.

One purpose of image and/or video coding and decoding can be thereduction of redundancy in the input image and/or video signal, throughcompression. Compression can help reduce the aforementioned bandwidthand/or storage space requirements, in some cases by two orders ofmagnitude or more. Although the descriptions herein use videoencoding/decoding as illustrative examples, the same techniques can beapplied to image encoding/decoding in similar fashion without departingfrom the spirit of the present disclosure. Both lossless compression andlossy compression, as well as a combination thereof can be employed.Lossless compression refers to techniques where an exact copy of theoriginal signal can be reconstructed from the compressed originalsignal. When using lossy compression, the reconstructed signal may notbe identical to the original signal, but the distortion between originaland reconstructed signals is small enough to make the reconstructedsignal useful for the intended application. In the case of video, lossycompression is widely employed. The amount of distortion tolerateddepends on the application; for example, users of certain consumerstreaming applications may tolerate higher distortion than users oftelevision distribution applications. The compression ratio achievablecan reflect that: higher allowable/tolerable distortion can yield highercompression ratios.

A video encoder and decoder can utilize techniques from several broadcategories, including, for example, motion compensation, transformprocessing, quantization, and entropy coding.

Video codec technologies can include techniques known as intra coding.In intra coding, sample values are represented without reference tosamples or other data from previously reconstructed reference pictures.In some video codecs, the picture is spatially subdivided into blocks ofsamples. When all blocks of samples are coded in intra mode, thatpicture can be an intra picture. Intra pictures and their derivationssuch as independent decoder refresh pictures, can be used to reset thedecoder state and can, therefore, be used as the first picture in acoded video bitstream and a video session, or as a still image. Thesamples of an intra block can be exposed to a transform, and thetransform coefficients can be quantized before entropy coding. Intraprediction can be a technique that minimizes sample values in thepre-transform domain. In some cases, the smaller the DC value after atransform is, and the smaller the AC coefficients are, the fewer thebits that are required at a given quantization step size to representthe block after entropy coding.

Traditional intra coding used in, for example, MPEG-2 generation codingtechnologies, does not use intra prediction. However, some newer videocompression technologies include techniques that attempt to performprediction based on, for example, surrounding sample data and/ormetadata obtained during the encoding and/or decoding of blocks of data.Such techniques are henceforth called “intra prediction” techniques.Note that in at least some cases, intra prediction is using referencedata only from the current picture under reconstruction and not fromreference pictures.

There can be many different forms of intra prediction. When more thanone of such techniques can be used in a given video coding technology, aspecific technique in use can be coded as a specific intra predictionmode that uses the specific technique. In certain cases, intraprediction modes can have submodes and/or parameters, where the submodesand/or parameters can be coded individually or included in a modecodeword, which defines the prediction mode being used. Which codewordto use for a given mode, submode, and/or parameter combination can havean impact in the coding efficiency gain through intra prediction, and socan the entropy coding technology used to translate the codewords into abitstream.

A certain mode of intra prediction was introduced with H.264, refined inH.265, and further refined in newer coding technologies such as jointexploration model (JEM), versatile video coding (VVC), and benchmark set(BMS). A predictor block can be formed using neighboring sample valuesof already available samples. Sample values of neighboring samples arecopied into the predictor block according to a direction. A reference tothe direction in use can be coded in the bitstream or may itself bepredicted.

Referring to FIG. 1A, depicted in the lower right is a subset of ninepredictor directions known from the 33 possible predictor directions(corresponding to the 33 angular modes of the 35 intra modes) defined inH.265. The point where the arrows converge (101) represents the samplebeing predicted. The arrows represent the direction from which thesample is being predicted. For example, arrow (102) indicates thatsample (101) is predicted from a sample or samples to the upper right,at a 45 degree angle from the horizontal. Similarly, arrow (103)indicates that sample (101) is predicted from a sample or samples to thelower left of sample (101), in a 22.5 degree angle from the horizontal.

Still referring to FIG. 1A, on the top left there is depicted a squareblock (104) of 4×4 samples (indicated by a dashed, boldface line). Thesquare block (104) includes 16 samples, each labelled with an “S”, itsposition in the Y dimension (e.g., row index) and its position in the Xdimension (e.g., column index). For example, sample S21 is the secondsample in the Y dimension (from the top) and the first (from the left)sample in the X dimension. Similarly, sample S44 is the fourth sample inblock (104) in both the Y and X dimensions. As the block is 4×4 samplesin size, S44 is at the bottom right. Further shown are reference samplesthat follow a similar numbering scheme. A reference sample is labelledwith an R, its Y position (e.g., row index) and X position (columnindex) relative to block (104). In both H.264 and H.265, predictionsamples neighbor the block under reconstruction; therefore, no negativevalues need to be used.

Intra picture prediction can work by copying reference sample valuesfrom the neighboring samples indicated by the signaled predictiondirection. For example, assume the coded video bitstream includessignaling that, for this block, indicates a prediction directionconsistent with arrow (102)—that is, samples are predicted from samplesto the upper right, at a 45 degree angle from the horizontal. In thatcase, samples S41, S32, S23, and S14 are predicted from the samereference sample R05. Sample S44 is then predicted from reference sampleR08.

In certain cases, the values of multiple reference samples may becombined, for example through interpolation, in order to calculate areference sample; especially when the directions are not evenlydivisible by 45 degrees.

The number of possible directions has increased as video codingtechnology has developed. In H.264 (year 2003), nine different directioncould be represented. That increased to 33 in H.265 (year 2013).Currently, JEM/VVC/BMS can support up to 65 directions. Experiments havebeen conducted to identify the most likely directions, and certaintechniques in the entropy coding are used to represent those likelydirections in a small number of bits, accepting a certain penalty forless likely directions. Further, the directions themselves can sometimesbe predicted from neighboring directions used in neighboring, alreadydecoded, blocks.

FIG. 1B shows a schematic (110) that depicts 65 intra predictiondirections according to JEM to illustrate the increasing number ofprediction directions over time.

The mapping of intra prediction direction bits that represent thedirection in the coded video bitstream can be different from videocoding technology to video coding technology. Such mapping can range,for example, from simple direct mappings, to codewords, to complexadaptive schemes involving most probable modes, and similar techniques.In most cases, however, there can be certain directions that arestatistically less likely to occur in video content than certain otherdirections. As the goal of video compression is the reduction ofredundancy, those less likely directions will, in a well working videocoding technology, be represented by a larger number of bits than morelikely directions.

Image and/or video coding and decoding can be performed usinginter-picture prediction with motion compensation. Motion compensationcan be a lossy compression technique and can relate to techniques wherea block of sample data from a previously reconstructed picture or partthereof (reference picture), after being spatially shifted in adirection indicated by a motion vector (MV henceforth), is used for theprediction of a newly reconstructed picture or picture part. In somecases, the reference picture can be the same as the picture currentlyunder reconstruction. MVs can have two dimensions X and Y, or threedimensions, the third being an indication of the reference picture inuse (the latter, indirectly, can be a time dimension).

In some video compression techniques, an MV applicable to a certain areaof sample data can be predicted from other MVs, for example from thoserelated to another area of sample data spatially adjacent to the areaunder reconstruction, and preceding that MV in decoding order. Doing socan substantially reduce the amount of data required for coding the MV,thereby removing redundancy and increasing compression. MV predictioncan work effectively, for example, because when coding an input videosignal derived from a camera (known as natural video) there is astatistical likelihood that areas larger than the area to which a singleMV is applicable move in a similar direction and, therefore, can in somecases be predicted using a similar motion vector derived from MVs ofneighboring area. That results in the MV found for a given area to besimilar or the same as the MV predicted from the surrounding MVs, andthat in turn can be represented, after entropy coding, in a smallernumber of bits than what would be used if coding the MV directly. Insome cases, MV prediction can be an example of lossless compression of asignal (namely: the MVs) derived from the original signal (namely: thesample stream). In other cases, MV prediction itself can be lossy, forexample because of rounding errors when calculating a predictor fromseveral surrounding MVs.

Various MV prediction mechanisms are described in H.265/HEVC (ITU-T Rec.H.265, “High Efficiency Video Coding”, December 2016). Out of the manyMV prediction mechanisms that H.265 offers, described with reference toFIG. 2 is a technique henceforth referred to as “spatial merge”.

Referring to FIG. 2 , a current block (201) comprises samples that havebeen found by the encoder during the motion search process to bepredictable from a previous block of the same size that has beenspatially shifted. Instead of coding that MV directly, the MV can bederived from metadata associated with one or more reference pictures,for example from the most recent (in decoding order) reference picture,using the MV associated with either one of five surrounding samples,denoted A0, A1, and B0, B1, B2 (202 through 206, respectively). InH.265, the MV prediction can use predictors from the same referencepicture that the neighboring block is using.

SUMMARY

Aspects of the disclosure provide methods and apparatuses for videoencoding/decoding. In some examples, an apparatus for video decodingincludes receiving circuitry and processing circuitry. The processingcircuitry decodes prediction information of a chroma block to bereconstructed in a current picture. The prediction information indicatesthat a cross-component linear model (CCLM) mode is applied to the chromablock. For a first region in the chroma block, a first adjustmentparameter used to adjust an offset parameter in the CCLM mode can bedetermined based on a first subset of reconstructed samples in acollocated luma block in the current picture. The first subset of thereconstructed samples does not include one or more samples in thecollocated luma block. A first updated offset parameter of the firstregion in the chroma block can be determined based at least on theoffset parameter and the first adjustment parameter. The first region inthe chroma block can be reconstructed based at least on the firstupdated offset parameter using the CCLM mode.

In an example, the first region in the chroma block includes the entirechroma block. The first subset of the reconstructed samples in thecollocated luma block is one sample in the collocated luma block. Thefirst adjustment parameter can be determined to be a sample value of theone sample in the collocated luma block.

In an example, the first region includes the entire chroma block. Thefirst subset of the reconstructed samples includes a plurality ofsamples in the collocated luma block. The first adjustment parameter canbe determined to be an average of sample values of the plurality ofsamples in the collocated luma block.

In an example, the first region includes the entire chroma block. Theprediction information further indicates which of the samples in thecollocated luma block is included in the first subset of thereconstructed samples.

In an example, the chroma block further includes a second region. Thefirst subset of the reconstructed samples is a first sample in thecollocated luma block. For the second region in the chroma block, asecond adjustment parameter used to adjust the offset parameter in theCCLM mode can be determined based on a second sample in the collocatedluma block. In an example, the second sample is different from the firstsample. A second updated offset parameter of the second region can bedetermined based at least on the offset parameter and the secondadjustment parameter. The second region in the chroma block can bereconstructed based at least on the second updated offset parameterusing the CCLM mode.

In an example, the collocated luma block includes a first luma regionand a second luma region that are collocated with the first region andthe second region in the chroma block, respectively. The first subset ofthe reconstructed samples includes a plurality of samples in the firstluma region. For the second region in the chroma block, a secondadjustment parameter used to adjust the offset parameter in the CCLMmode can be determined based on a plurality of samples in the secondluma region. A second updated offset parameter of the second region canbe determined based at least on the offset parameter and the secondadjustment parameter. The second region in the chroma block can bereconstructed based at least on the second updated offset parameterusing the CCLM mode.

In an example, the first subset of the reconstructed samples includes atop-left sample, a top-right sample, a bottom-left sample, and abottom-right sample in the first luma region. The first adjustmentparameter can be determined to be an average of the top-left sample, thetop-right sample, the bottom-left sample, and the bottom-right sample inthe first luma region. For the second region in the chroma block, asecond adjustment parameter used to adjust the offset parameter in theCCLM mode can be determined to be an average of a top-left sample, atop-right sample, a bottom-left sample, and a bottom-right sample in thesecond luma region. A second updated offset parameter of the secondregion can be determined based at least on the second offset parameterand the second adjustment parameter. The second region in the chromablock can be reconstructed based at least on the second updated offsetparameter using the CCLM mode.

In an example, for the first region, an updated scaling parameter can bedetermined to be a sum of a scaling parameter used in the CCLM mode andan adjustment parameter used to adjust the scaling parameter. The firstupdated offset parameter can be determined to be (b−u×y_(r)) where b isthe offset parameter, u is the adjustment parameter used to adjust thescaling parameter, and y_(r) is the first adjustment parameter. Thefirst region in the chroma block can be reconstructed based on the firstupdated offset parameter and the updated scaling parameter using theCCLM mode.

In an example, for the first region, the adjustment parameter used toadjust the scaling parameter is determined based on (i) reconstructedluma samples in one or more neighboring luma blocks of the collocatedluma block and (ii) samples in the collocated luma block.

In an example, for the first region, the adjustment parameter used toadjust the scaling parameter is determined based on a difference betweenan average of the reconstructed luma samples in the one or moreneighboring luma blocks and an average of the samples in the collocatedluma block.

In an embodiment, for a first region in the chroma block, the processingcircuitry determines a first adjustment value used to modify an offsetparameter in the CCLM mode based on a first subset of reconstructedsamples in a luma block that is collocated with the chroma block in thecurrent picture. The first subset of the reconstructed samples does notinclude one or more samples in the luma block. The processing circuitryupdates the offset parameter based at least on the first adjustmentvalue. The processing circuitry determines a second adjustment valueused to modify a slope parameter in the CCLM mode based on a secondsubset of the reconstructed samples in the luma block and updates theslope parameter based at least on the second adjustment value. Theprocessing circuitry can reconstruct the first region in the chromablock based at least on the updated offset parameter and the updatedslope parameter using the CCLM mode.

In an example, the second subset of the reconstructed samples includesthe first subset of the reconstructed samples.

In an example, the processing circuitry determines the second adjustmentvalue based on the reconstructed samples in the entire luma block.

Aspects of the disclosure also provide a non-transitorycomputer-readable medium storing instructions which when executed by acomputer for video decoding cause the computer to perform the method forvideo decoding.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1A is a schematic illustration of an exemplary subset of intraprediction modes.

FIG. 1B is an illustration of exemplary intra prediction directions.

FIG. 2 shows an example of a current block (201) and surroundingsamples.

FIG. 3 is a schematic illustration of an exemplary block diagram of acommunication system (300).

FIG. 4 is a schematic illustration of an exemplary block diagram of acommunication system (400).

FIG. 5 is a schematic illustration of an exemplary block diagram of adecoder.

FIG. 6 is a schematic illustration of an exemplary block diagram of anencoder.

FIG. 7 shows a block diagram of an exemplary encoder.

FIG. 8 shows a block diagram of an exemplary decoder.

FIG. 9 shows exemplary reference samples of a current block.

FIG. 10 shows examples of reconstructed neighboring luma samples andreconstructed neighboring chroma samples used in a cross-componentlinear model (CCLM) mode.

FIG. 11 shows examples of reconstructed neighboring luma samples andreconstructed neighboring chroma samples used in the CCLM mode.

FIGS. 12A-12B show examples of parameter adjustments used in the CCLMmode.

FIG. 13 shows examples of sample positions of selected luma samples in acollocated luma block used to determine an adjustment parameter.

FIG. 14 shows an exemplary chroma block and a collocated luma block.

FIG. 15 shows an exemplary chroma block and a collocated luma block.

FIG. 16 shows a flow chart outlining an encoding process according tosome embodiments of the disclosure.

FIG. 17 shows a flow chart outlining a decoding process according tosome embodiments of the disclosure.

FIG. 18 is a schematic illustration of a computer system in accordancewith an embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

FIG. 3 illustrates an exemplary block diagram of a communication system(300). The communication system (300) includes a plurality of terminaldevices that can communicate with each other, via, for example, anetwork (350). For example, the communication system (300) includes afirst pair of terminal devices (310) and (320) interconnected via thenetwork (350). In the FIG. 3 example, the first pair of terminal devices(310) and (320) performs unidirectional transmission of data. Forexample, the terminal device (310) may code video data (e.g., a streamof video pictures that are captured by the terminal device (310)) fortransmission to the other terminal device (320) via the network (350).The encoded video data can be transmitted in the form of one or morecoded video bitstreams. The terminal device (320) may receive the codedvideo data from the network (350), decode the coded video data torecover the video pictures and display video pictures according to therecovered video data. Unidirectional data transmission may be common inmedia serving applications and the like.

In another example, the communication system (300) includes a secondpair of terminal devices (330) and (340) that perform bidirectionaltransmission of coded video data, for example, during videoconferencing.For bidirectional transmission of data, in an example, each terminaldevice of the terminal devices (330) and (340) may code video data(e.g., a stream of video pictures that are captured by the terminaldevice) for transmission to the other terminal device of the terminaldevices (330) and (340) via the network (350). Each terminal device ofthe terminal devices (330) and (340) also may receive the coded videodata transmitted by the other terminal device of the terminal devices(330) and (340), and may decode the coded video data to recover thevideo pictures and may display video pictures at an accessible displaydevice according to the recovered video data.

In the example of FIG. 3 , the terminal devices (310), (320), (330) and(340) are respectively illustrated as servers, personal computers andsmart phones but the principles of the present disclosure may be not solimited. Embodiments of the present disclosure find application withlaptop computers, tablet computers, media players, and/or dedicatedvideo conferencing equipment. The network (350) represents any number ofnetworks that convey coded video data among the terminal devices (310),(320), (330) and (340), including for example wireline (wired) and/orwireless communication networks. The communication network (350) mayexchange data in circuit-switched and/or packet-switched channels.Representative networks include telecommunications networks, local areanetworks, wide area networks and/or the Internet. For the purposes ofthe present discussion, the architecture and topology of the network(350) may be immaterial to the operation of the present disclosureunless explained herein below.

FIG. 4 illustrates, as an example of an application for the disclosedsubject matter, a video encoder and a video decoder in a streamingenvironment. The disclosed subject matter can be equally applicable toother video enabled applications, including, for example, videoconferencing, digital TV, streaming services, storing of compressedvideo on digital media including CD, DVD, memory stick and the like, andso on.

A streaming system may include a capture subsystem (413), that caninclude a video source (401), for example a digital camera, creating forexample a stream of video pictures (402) that are uncompressed. In anexample, the stream of video pictures (402) includes samples that aretaken by the digital camera. The stream of video pictures (402),depicted as a bold line to emphasize a high data volume when compared toencoded video data (404) (or coded video bitstreams), can be processedby an electronic device (420) that includes a video encoder (403)coupled to the video source (401). The video encoder (403) can includehardware, software, or a combination thereof to enable or implementaspects of the disclosed subject matter as described in more detailbelow. The encoded video data (404) (or encoded video bitstream),depicted as a thin line to emphasize the lower data volume when comparedto the stream of video pictures (402), can be stored on a streamingserver (405) for future use. One or more streaming client subsystems,such as client subsystems (406) and (408) in FIG. 4 can access thestreaming server (405) to retrieve copies (407) and (409) of the encodedvideo data (404). A client subsystem (406) can include a video decoder(410), for example, in an electronic device (430). The video decoder(410) decodes the incoming copy (407) of the encoded video data andcreates an outgoing stream of video pictures (411) that can be renderedon a display (412) (e.g., display screen) or other rendering device (notdepicted). In some streaming systems, the encoded video data (404),(407), and (409) (e.g., video bitstreams) can be encoded according tocertain video coding/compression standards. Examples of those standardsinclude ITU-T Recommendation H.265. In an example, a video codingstandard under development is informally known as Versatile Video Coding(VVC). The disclosed subject matter may be used in the context of VVC.

It is noted that the electronic devices (420) and (430) can includeother components (not shown). For example, the electronic device (420)can include a video decoder (not shown) and the electronic device (430)can include a video encoder (not shown) as well.

FIG. 5 shows an exemplary block diagram of a video decoder (510). Thevideo decoder (510) can be included in an electronic device (530). Theelectronic device (530) can include a receiver (531) (e.g., receivingcircuitry). The video decoder (510) can be used in the place of thevideo decoder (410) in the FIG. 4 example.

The receiver (531) may receive one or more coded video sequences to bedecoded by the video decoder (510). In an embodiment, one coded videosequence is received at a time, where the decoding of each coded videosequence is independent from the decoding of other coded videosequences. The coded video sequence may be received from a channel(501), which may be a hardware/software link to a storage device whichstores the encoded video data. The receiver (531) may receive theencoded video data with other data, for example, coded audio data and/orancillary data streams, that may be forwarded to their respective usingentities (not depicted). The receiver (531) may separate the coded videosequence from the other data. To combat network jitter, a buffer memory(515) may be coupled in between the receiver (531) and an entropydecoder/parser (520) (“parser (520)” henceforth). In certainapplications, the buffer memory (515) is part of the video decoder(510). In others, it can be outside of the video decoder (510) (notdepicted). In still others, there can be a buffer memory (not depicted)outside of the video decoder (510), for example to combat networkjitter, and in addition another buffer memory (515) inside the videodecoder (510), for example to handle playout timing. When the receiver(531) is receiving data from a store/forward device of sufficientbandwidth and controllability, or from an isosynchronous network, thebuffer memory (515) may not be needed, or can be small. For use on besteffort packet networks such as the Internet, the buffer memory (515) maybe required, can be comparatively large and can be advantageously ofadaptive size, and may at least partially be implemented in an operatingsystem or similar elements (not depicted) outside of the video decoder(510).

The video decoder (510) may include the parser (520) to reconstructsymbols (521) from the coded video sequence. Categories of those symbolsinclude information used to manage operation of the video decoder (510),and potentially information to control a rendering device such as arender device (512) (e.g., a display screen) that is not an integralpart of the electronic device (530) but can be coupled to the electronicdevice (530), as shown in FIG. 5 . The control information for therendering device(s) may be in the form of Supplemental EnhancementInformation (SEI) messages or Video Usability Information (VUI)parameter set fragments (not depicted). The parser (520) mayparse/entropy-decode the coded video sequence that is received. Thecoding of the coded video sequence can be in accordance with a videocoding technology or standard, and can follow various principles,including variable length coding, Huffman coding, arithmetic coding withor without context sensitivity, and so forth. The parser (520) mayextract from the coded video sequence, a set of subgroup parameters forat least one of the subgroups of pixels in the video decoder, based uponat least one parameter corresponding to the group. Subgroups can includeGroups of Pictures (GOPs), pictures, tiles, slices, macroblocks, CodingUnits (CUs), blocks, Transform Units (TUs), Prediction Units (PUs) andso forth. The parser (520) may also extract from the coded videosequence information such as transform coefficients, quantizer parametervalues, motion vectors, and so forth.

The parser (520) may perform an entropy decoding/parsing operation onthe video sequence received from the buffer memory (515), so as tocreate symbols (521).

Reconstruction of the symbols (521) can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by subgroup controlinformation parsed from the coded video sequence by the parser (520).The flow of such subgroup control information between the parser (520)and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, the video decoder (510)can be conceptually subdivided into a number of functional units asdescribed below. In a practical implementation operating undercommercial constraints, many of these units interact closely with eachother and can, at least partly, be integrated into each other. However,for the purpose of describing the disclosed subject matter, theconceptual subdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit (551). Thescaler/inverse transform unit (551) receives a quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) (521) from the parser (520). The scaler/inversetransform unit (551) can output blocks comprising sample values, thatcan be input into aggregator (555).

In some cases, the output samples of the scaler/inverse transform unit(551) can pertain to an intra coded block. The intra coded block is ablock that is not using predictive information from previouslyreconstructed pictures, but can use predictive information frompreviously reconstructed parts of the current picture. Such predictiveinformation can be provided by an intra picture prediction unit (552).In some cases, the intra picture prediction unit (552) generates a blockof the same size and shape of the block under reconstruction, usingsurrounding already reconstructed information fetched from the currentpicture buffer (558). The current picture buffer (558) buffers, forexample, partly reconstructed current picture and/or fully reconstructedcurrent picture. The aggregator (555), in some cases, adds, on a persample basis, the prediction information the intra prediction unit (552)has generated to the output sample information as provided by thescaler/inverse transform unit (551).

In other cases, the output samples of the scaler/inverse transform unit(551) can pertain to an inter coded, and potentially motion compensated,block. In such a case, a motion compensation prediction unit (553) canaccess reference picture memory (557) to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols (521) pertaining to the block, these samples can beadded by the aggregator (555) to the output of the scaler/inversetransform unit (551) (in this case called the residual samples orresidual signal) so as to generate output sample information. Theaddresses within the reference picture memory (557) from where themotion compensation prediction unit (553) fetches prediction samples canbe controlled by motion vectors, available to the motion compensationprediction unit (553) in the form of symbols (521) that can have, forexample X, Y, and reference picture components. Motion compensation alsocan include interpolation of sample values as fetched from the referencepicture memory (557) when sub-sample exact motion vectors are in use,motion vector prediction mechanisms, and so forth.

The output samples of the aggregator (555) can be subject to variousloop filtering techniques in the loop filter unit (556). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video sequence (alsoreferred to as coded video bitstream) and made available to the loopfilter unit (556) as symbols (521) from the parser (520). Videocompression can also be responsive to meta-information obtained duringthe decoding of previous (in decoding order) parts of the coded pictureor coded video sequence, as well as responsive to previouslyreconstructed and loop-filtered sample values.

The output of the loop filter unit (556) can be a sample stream that canbe output to the render device (512) as well as stored in the referencepicture memory (557) for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. For example, once a codedpicture corresponding to a current picture is fully reconstructed andthe coded picture has been identified as a reference picture (by, forexample, the parser (520)), the current picture buffer (558) can becomea part of the reference picture memory (557), and a fresh currentpicture buffer can be reallocated before commencing the reconstructionof the following coded picture.

The video decoder (510) may perform decoding operations according to apredetermined video compression technology or a standard, such as ITU-TRec. H.265. The coded video sequence may conform to a syntax specifiedby the video compression technology or standard being used, in the sensethat the coded video sequence adheres to both the syntax of the videocompression technology or standard and the profiles as documented in thevideo compression technology or standard. Specifically, a profile canselect certain tools as the only tools available for use under thatprofile from all the tools available in the video compression technologyor standard. Also necessary for compliance can be that the complexity ofthe coded video sequence is within bounds as defined by the level of thevideo compression technology or standard. In some cases, levels restrictthe maximum picture size, maximum frame rate, maximum reconstructionsample rate (measured in, for example megasamples per second), maximumreference picture size, and so on. Limits set by levels can, in somecases, be further restricted through Hypothetical Reference Decoder(HRD) specifications and metadata for HRD buffer management signaled inthe coded video sequence.

In an embodiment, the receiver (531) may receive additional (redundant)data with the encoded video. The additional data may be included as partof the coded video sequence(s). The additional data may be used by thevideo decoder (510) to properly decode the data and/or to moreaccurately reconstruct the original video data. Additional data can bein the form of, for example, temporal, spatial, or signal noise ratio(SNR) enhancement layers, redundant slices, redundant pictures, forwarderror correction codes, and so on.

FIG. 6 shows an exemplary block diagram of a video encoder (603). Thevideo encoder (603) is included in an electronic device (620). Theelectronic device (620) includes a transmitter (640) (e.g., transmittingcircuitry). The video encoder (603) can be used in the place of thevideo encoder (403) in the FIG. 4 example.

The video encoder (603) may receive video samples from a video source(601) (that is not part of the electronic device (620) in the FIG. 6example) that may capture video image(s) to be coded by the videoencoder (603). In another example, the video source (601) is a part ofthe electronic device (620).

The video source (601) may provide the source video sequence to be codedby the video encoder (603) in the form of a digital video sample streamthat can be of any suitable bit depth (for example: 8 bit, 10 bit, 12bit, . . . ), any colorspace (for example, BT.601 Y CrCB, RGB, . . . ),and any suitable sampling structure (for example Y CrCb 4:2:0, Y CrCb4:4:4). In a media serving system, the video source (601) may be astorage device storing previously prepared video. In a videoconferencingsystem, the video source (601) may be a camera that captures local imageinformation as a video sequence. Video data may be provided as aplurality of individual pictures that impart motion when viewed insequence. The pictures themselves may be organized as a spatial array ofpixels, wherein each pixel can comprise one or more samples depending onthe sampling structure, color space, etc. in use. A person skilled inthe art can readily understand the relationship between pixels andsamples. The description below focuses on samples.

According to an embodiment, the video encoder (603) may code andcompress the pictures of the source video sequence into a coded videosequence (643) in real time or under any other time constraints asrequired. Enforcing appropriate coding speed is one function of acontroller (650). In some embodiments, the controller (650) controlsother functional units as described below and is functionally coupled tothe other functional units. The coupling is not depicted for clarity.Parameters set by the controller (650) can include rate control relatedparameters (picture skip, quantizer, lambda value of rate-distortionoptimization techniques, . . . ), picture size, group of pictures (GOP)layout, maximum motion vector search range, and so forth. The controller(650) can be configured to have other suitable functions that pertain tothe video encoder (603) optimized for a certain system design.

In some embodiments, the video encoder (603) is configured to operate ina coding loop. As an oversimplified description, in an example, thecoding loop can include a source coder (630) (e.g., responsible forcreating symbols, such as a symbol stream, based on an input picture tobe coded, and a reference picture(s)), and a (local) decoder (633)embedded in the video encoder (603). The decoder (633) reconstructs thesymbols to create the sample data in a similar manner as a (remote)decoder also would create. The reconstructed sample stream (sample data)is input to the reference picture memory (634). As the decoding of asymbol stream leads to bit-exact results independent of decoder location(local or remote), the content in the reference picture memory (634) isalso bit exact between the local encoder and remote encoder. In otherwords, the prediction part of an encoder “sees” as reference picturesamples exactly the same sample values as a decoder would “see” whenusing prediction during decoding. This fundamental principle ofreference picture synchronicity (and resulting drift, if synchronicitycannot be maintained, for example because of channel errors) is used insome related arts as well.

The operation of the “local” decoder (633) can be the same as of a“remote” decoder, such as the video decoder (510), which has alreadybeen described in detail above in conjunction with FIG. 5 . Brieflyreferring also to FIG. 5 , however, as symbols are available andencoding/decoding of symbols to a coded video sequence by an entropycoder (645) and the parser (520) can be lossless, the entropy decodingparts of the video decoder (510), including the buffer memory (515), andparser (520) may not be fully implemented in the local decoder (633).

In an embodiment, a decoder technology except the parsing/entropydecoding that is present in a decoder is present, in an identical or asubstantially identical functional form, in a corresponding encoder.Accordingly, the disclosed subject matter focuses on decoder operation.The description of encoder technologies can be abbreviated as they arethe inverse of the comprehensively described decoder technologies. Incertain areas a more detail description is provided below.

During operation, in some examples, the source coder (630) may performmotion compensated predictive coding, which codes an input picturepredictively with reference to one or more previously coded picture fromthe video sequence that were designated as “reference pictures.” In thismanner, the coding engine (632) codes differences between pixel blocksof an input picture and pixel blocks of reference picture(s) that may beselected as prediction reference(s) to the input picture.

The local video decoder (633) may decode coded video data of picturesthat may be designated as reference pictures, based on symbols createdby the source coder (630). Operations of the coding engine (632) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 6 ), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (633) replicates decodingprocesses that may be performed by the video decoder on referencepictures and may cause reconstructed reference pictures to be stored inthe reference picture memory (634). In this manner, the video encoder(603) may store copies of reconstructed reference pictures locally thathave common content as the reconstructed reference pictures that will beobtained by a far-end video decoder (absent transmission errors).

The predictor (635) may perform prediction searches for the codingengine (632). That is, for a new picture to be coded, the predictor(635) may search the reference picture memory (634) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(635) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (635), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (634).

The controller (650) may manage coding operations of the source coder(630), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (645). The entropy coder (645)translates the symbols as generated by the various functional units intoa coded video sequence, by applying lossless compression to the symbolsaccording to technologies such as Huffman coding, variable lengthcoding, arithmetic coding, and so forth.

The transmitter (640) may buffer the coded video sequence(s) as createdby the entropy coder (645) to prepare for transmission via acommunication channel (660), which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter(640) may merge coded video data from the video encoder (603) with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller (650) may manage operation of the video encoder (603).During coding, the controller (650) may assign to each coded picture acertain coded picture type, which may affect the coding techniques thatmay be applied to the respective picture. For example, pictures oftenmay be assigned as one of the following picture types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other picture in the sequence as a source ofprediction. Some video codecs allow for different types of intrapictures, including, for example Independent Decoder Refresh (“IDR”)Pictures. A person skilled in the art is aware of those variants of Ipictures and their respective applications and features.

A predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A bi-directionally predictive picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded predictively, viaspatial prediction or via temporal prediction with reference to onepreviously coded reference picture. Blocks of B pictures may be codedpredictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video encoder (603) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video encoder (603) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data, therefore, may conform to a syntax specified bythe video coding technology or standard being used.

In an embodiment, the transmitter (640) may transmit additional datawith the encoded video. The source coder (630) may include such data aspart of the coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, SEI messages, VUI parameter setfragments, and so on.

A video may be captured as a plurality of source pictures (videopictures) in a temporal sequence. Intra-picture prediction (oftenabbreviated to intra prediction) makes use of spatial correlation in agiven picture, and inter-picture prediction makes uses of the (temporalor other) correlation between the pictures. In an example, a specificpicture under encoding/decoding, which is referred to as a currentpicture, is partitioned into blocks. When a block in the current pictureis similar to a reference block in a previously coded and still bufferedreference picture in the video, the block in the current picture can becoded by a vector that is referred to as a motion vector. The motionvector points to the reference block in the reference picture, and canhave a third dimension identifying the reference picture, in casemultiple reference pictures are in use.

In some embodiments, a bi-prediction technique can be used in theinter-picture prediction. According to the bi-prediction technique, tworeference pictures, such as a first reference picture and a secondreference picture that are both prior in decoding order to the currentpicture in the video (but may be in the past and future, respectively,in display order) are used. A block in the current picture can be codedby a first motion vector that points to a first reference block in thefirst reference picture, and a second motion vector that points to asecond reference block in the second reference picture. The block can bepredicted by a combination of the first reference block and the secondreference block.

Further, a merge mode technique can be used in the inter-pictureprediction to improve coding efficiency.

According to some embodiments of the disclosure, predictions, such asinter-picture predictions and intra-picture predictions, are performedin the unit of blocks. For example, according to the HEVC standard, apicture in a sequence of video pictures is partitioned into coding treeunits (CTU) for compression, the CTUs in a picture have the same size,such as 64×64 pixels, 32×32 pixels, or 16×16 pixels. In general, a CTUincludes three coding tree blocks (CTBs), which are one luma CTB and twochroma CTBs. Each CTU can be recursively quadtree split into one ormultiple coding units (CUs). For example, a CTU of 64×64 pixels can besplit into one CU of 64×64 pixels, or 4 CUs of 32×32 pixels, or 16 CUsof 16×16 pixels. In an example, each CU is analyzed to determine aprediction type for the CU, such as an inter prediction type or an intraprediction type. The CU is split into one or more prediction units (PUs)depending on the temporal and/or spatial predictability. Generally, eachPU includes a luma prediction block (PB), and two chroma PBs. In anembodiment, a prediction operation in coding (encoding/decoding) isperformed in the unit of a prediction block. Using a luma predictionblock as an example of a prediction block, the prediction block includesa matrix of values (e.g., luma values) for pixels, such as 8×8 pixels,16×16 pixels, 8×16 pixels, 16×8 pixels, and the like.

FIG. 7 shows an exemplary diagram of a video encoder (703). The videoencoder (703) is configured to receive a processing block (e.g., aprediction block) of sample values within a current video picture in asequence of video pictures, and encode the processing block into a codedpicture that is part of a coded video sequence. In an example, the videoencoder (703) is used in the place of the video encoder (403) in theFIG. 4 example.

In an HEVC example, the video encoder (703) receives a matrix of samplevalues for a processing block, such as a prediction block of 8×8samples, and the like. The video encoder (703) determines whether theprocessing block is best coded using intra mode, inter mode, orbi-prediction mode using, for example, rate-distortion optimization.When the processing block is to be coded in intra mode, the videoencoder (703) may use an intra prediction technique to encode theprocessing block into the coded picture; and when the processing blockis to be coded in inter mode or bi-prediction mode, the video encoder(703) may use an inter prediction or bi-prediction technique,respectively, to encode the processing block into the coded picture. Incertain video coding technologies, merge mode can be an inter pictureprediction submode where the motion vector is derived from one or moremotion vector predictors without the benefit of a coded motion vectorcomponent outside the predictors. In certain other video codingtechnologies, a motion vector component applicable to the subject blockmay be present. In an example, the video encoder (703) includes othercomponents, such as a mode decision module (not shown) to determine themode of the processing blocks.

In the FIG. 7 example, the video encoder (703) includes an inter encoder(730), an intra encoder (722), a residue calculator (723), a switch(726), a residue encoder (724), a general controller (721), and anentropy encoder (725) coupled together as shown in FIG. 7 .

The inter encoder (730) is configured to receive the samples of thecurrent block (e.g., a processing block), compare the block to one ormore reference blocks in reference pictures (e.g., blocks in previouspictures and later pictures), generate inter prediction information(e.g., description of redundant information according to inter encodingtechnique, motion vectors, merge mode information), and calculate interprediction results (e.g., predicted block) based on the inter predictioninformation using any suitable technique. In some examples, thereference pictures are decoded reference pictures that are decoded basedon the encoded video information.

The intra encoder (722) is configured to receive the samples of thecurrent block (e.g., a processing block), in some cases compare theblock to blocks already coded in the same picture, generate quantizedcoefficients after transform, and in some cases also generate intraprediction information (e.g., an intra prediction direction informationaccording to one or more intra encoding techniques). In an example, theintra encoder (722) also calculates intra prediction results (e.g.,predicted block) based on the intra prediction information and referenceblocks in the same picture.

The general controller (721) is configured to determine general controldata and control other components of the video encoder (703) based onthe general control data. In an example, the general controller (721)determines the mode of the block, and provides a control signal to theswitch (726) based on the mode. For example, when the mode is the intramode, the general controller (721) controls the switch (726) to selectthe intra mode result for use by the residue calculator (723), andcontrols the entropy encoder (725) to select the intra predictioninformation and include the intra prediction information in thebitstream; and when the mode is the inter mode, the general controller(721) controls the switch (726) to select the inter prediction resultfor use by the residue calculator (723), and controls the entropyencoder (725) to select the inter prediction information and include theinter prediction information in the bitstream.

The residue calculator (723) is configured to calculate a difference(residue data) between the received block and prediction resultsselected from the intra encoder (722) or the inter encoder (730). Theresidue encoder (724) is configured to operate based on the residue datato encode the residue data to generate the transform coefficients. In anexample, the residue encoder (724) is configured to convert the residuedata from a spatial domain to a frequency domain, and generate thetransform coefficients. The transform coefficients are then subject toquantization processing to obtain quantized transform coefficients. Invarious embodiments, the video encoder (703) also includes a residuedecoder (728). The residue decoder (728) is configured to performinverse-transform, and generate the decoded residue data. The decodedresidue data can be suitably used by the intra encoder (722) and theinter encoder (730). For example, the inter encoder (730) can generatedecoded blocks based on the decoded residue data and inter predictioninformation, and the intra encoder (722) can generate decoded blocksbased on the decoded residue data and the intra prediction information.The decoded blocks are suitably processed to generate decoded picturesand the decoded pictures can be buffered in a memory circuit (not shown)and used as reference pictures in some examples.

The entropy encoder (725) is configured to format the bitstream toinclude the encoded block. The entropy encoder (725) is configured toinclude various information in the bitstream according to a suitablestandard, such as the HEVC standard. In an example, the entropy encoder(725) is configured to include the general control data, the selectedprediction information (e.g., intra prediction information or interprediction information), the residue information, and other suitableinformation in the bitstream. Note that, according to the disclosedsubject matter, when coding a block in the merge submode of either intermode or bi-prediction mode, there is no residue information.

FIG. 8 shows an exemplary diagram of a video decoder (810). The videodecoder (810) is configured to receive coded pictures that are part of acoded video sequence, and decode the coded pictures to generatereconstructed pictures. In an example, the video decoder (810) is usedin the place of the video decoder (410) in the FIG. 4 example.

In the FIG. 8 example, the video decoder (810) includes an entropydecoder (871), an inter decoder (880), a residue decoder (873), areconstruction module (874), and an intra decoder (872) coupled togetheras shown in FIG. 8 .

The entropy decoder (871) can be configured to reconstruct, from thecoded picture, certain symbols that represent the syntax elements ofwhich the coded picture is made up. Such symbols can include, forexample, the mode in which a block is coded (such as, for example, intramode, inter mode, bi-predicted mode, the latter two in merge submode oranother submode) and prediction information (such as, for example, intraprediction information or inter prediction information) that canidentify certain sample or metadata that is used for prediction by theintra decoder (872) or the inter decoder (880), respectively. Thesymbols can also include residual information in the form of, forexample, quantized transform coefficients, and the like. In an example,when the prediction mode is inter or bi-predicted mode, the interprediction information is provided to the inter decoder (880); and whenthe prediction type is the intra prediction type, the intra predictioninformation is provided to the intra decoder (872). The residualinformation can be subject to inverse quantization and is provided tothe residue decoder (873).

The inter decoder (880) is configured to receive the inter predictioninformation, and generate inter prediction results based on the interprediction information.

The intra decoder (872) is configured to receive the intra predictioninformation, and generate prediction results based on the intraprediction information.

The residue decoder (873) is configured to perform inverse quantizationto extract de-quantized transform coefficients, and process thede-quantized transform coefficients to convert the residual informationfrom the frequency domain to the spatial domain. The residue decoder(873) may also require certain control information (to include theQuantizer Parameter (QP)), and that information may be provided by theentropy decoder (871) (data path not depicted as this may be low volumecontrol information only).

The reconstruction module (874) is configured to combine, in the spatialdomain, the residual information as output by the residue decoder (873)and the prediction results (as output by the inter or intra predictionmodules as the case may be) to form a reconstructed block, that may bepart of the reconstructed picture, which in turn may be part of thereconstructed video. It is noted that other suitable operations, such asa deblocking operation and the like, can be performed to improve thevisual quality.

It is noted that the video encoders (403), (603), and (703), and thevideo decoders (410), (510), and (810) can be implemented using anysuitable technique. In an embodiment, the video encoders (403), (603),and (703), and the video decoders (410), (510), and (810) can beimplemented using one or more integrated circuits. In anotherembodiment, the video encoders (403), (603), and (603), and the videodecoders (410), (510), and (810) can be implemented using one or moreprocessors that execute software instructions.

In intra prediction or an intra prediction mode, sample values of acoding block can be predicted from neighboring samples that are alreadyreconstructed or reconstructed neighboring samples (referred to asreference samples).

An example of intra prediction is directional intra prediction. In thedirectional intra prediction, a sample (e.g., a current sample) in acurrent block can be predicted using a reference sample (e.g., aprediction sample) or an interpolated reference sample. For example, aconnected line between the current sample and the prediction sampleforms a given angle direction, such as used in an angular mode.

In another example of intra prediction, a planar mode that is based onsample interpolation is used. In the planar mode, one or more keypositions in or around the current block can be predicted usingneighboring reference samples. Other positions in the current block canbe predicted as a linear combination of sample(s) at the one or more keypositions and the reference samples. Weights (e.g., combination weights)may be determined according to a location of the current sample in thecurrent block.

An example of the planar mode, such as in VVC, is calculated below.

predV[x][y]=((H−1−y)×p[x][−1]+(y+1)×p[−1][H])«Log 2(W)  Eq. 1

predH[x][y]=((W−1−x)×p[−1][y]+(x+1)×p[W][−1])«Log 2(H)  Eq. 2

pred[x][y]=(predV[x][y]+predH[x][y]+W×H)»(Log 2(W)+Log 2(H)+1)  Eq. 3

Referring to FIG. 9 , a current block (900) includes samples atpositions (0, 0) to (H−1, W−1) in the current block (900). W and H are awidth and a height of the current block (900), respectively. A predictedsample value pred[x][y] of a current sample at a position (x, y) (x=0,1, . . . , or W−1, and y=0, 1, . . . , or H−1) in the current block(900) can be obtained as a weighted average of reference sample values(e.g., p[−1][y], p[x][−1], p[−1][H], and p[W][−1]) of reference sampleslocated at positions (−1, y), (x, −1), (−1, H), and (W, −1),respectively), as shown in Eqs. 1-3. The reference samples can includethe reference sample located at the position (−1, y) in the same row asthe current sample, the reference sample at the position (x, −1) in thesame column as the current sample, the reference sample at thebottom-left position (−1, H) with respect to the current block, and thereference sample at the top-right position (W, −1) with respect to thecurrent block.

As described above, the reference sample values of the reference samplescan include p[−1][y] of the reference sample located at the position(−1, y), p[x][−1] of the reference sample located at the position (x,−1), p[−1][H] of the reference sample located at the bottom-leftposition (−1, H), and p[W][−1] of the reference sample located at thetop-right position (W, −1). In an example shown in Eq. 1, a verticalpredictor predV[x][y] is determined based on the reference sampleslocated at the positions (x, −1) and (−1, H). In an example shown in Eq.2, a horizontal predictor predH[x][y] is determined based on thereference samples located at the positions (−1, y) and (W, −1). In Eq.3, the predicted sample value pred[x][y] is determined based on anaverage (e.g., a weighted average) of the horizontal predictorpredH[x][y] and the vertical predictor predV[x][y].

A cross-component linear model prediction (CCLM) mode is across-component prediction method. In the CCLM, chroma samples can bepredicted based on reconstructed luma samples using a linear model. Thelinear model can be built by neighboring already reconstructed samplesof a current block (e.g., a chroma block to be coded). In someembodiments, the prediction performance is high when the luma and chromachannels are highly linearly correlated.

In an embodiment, a chroma block (e.g., a current Cb block or a currentCr block) is predicted based on a collocated luma block. A predictionblock Pred_C of the chroma block can be derived as follows where asample Pred_C(x, y) in the prediction block Pred_C of the chroma blockcan be determined based on sample(s) in the collocated luma block thatis already reconstructed.

Pred_C(x,y)=a×Rec_L′(x,y)+b  Eq. 4

Pred_C(x, y) represents a predicted chroma sample at a sample location(x, y) of the chroma block (e.g., in a chroma channel of a currentpicture or a chroma picture). Rec_L′(x, y) can be determined fromreconstructed sample(s) in the collocated luma block (e.g., in a lumachannel of the current picture or a luma picture) that is alreadyreconstructed. Rec_L′ (x, y) can represent a reconstructed luma samplein the collocated luma block or a downsampled luma sample of thecollocated luma block.

In an example, Rec_L′ is the collocated luma block that is alreadyreconstructed, for example, when a color format is 4:4:4 and a size ofthe chroma block is identical to a size of the collocated luma block.Thus, Rec_L′(x, y) can represent a reconstructed sample in thecollocated luma block where the reconstructed sample corresponds to thesample location (x, y) of the chroma block.

In an example, Rec_L′ is different from the collocated luma block thatis already reconstructed. The current chroma block is collocated withthe collocated luma block, and the luma channel and the chroma channelhave different resolutions. In an example, when a color format is 4:2:0,the resolution of the luma block is two times that of the chroma blockboth vertically and horizontally. Therefore, when the color format is4:2:0, Rec_L′ can be a down-sampled block of the corresponding lumablock to match the chroma block size during the derivation of linearmodel. In some embodiments, the collocated luma block is down-sampledwhen the color format is not 4:4:4.

Parameters (e.g., model parameters) a and b in Eq. 4 can represent aslope and an offset in the linear model shown in Eq. 4, and can bereferred to as a slope parameter and an offset parameter, respectively.The parameters a and b in Eq. 4 can be derived from reconstructedneighboring samples (e.g., chroma samples and luma samples) around (i)the current chroma block in the chroma channel and (ii) the collocatedluma block in the luma channel. The parameters a and b can be determinedusing any suitable method.

In an example, the parameters a and b are determined with the classicallinear regression theory. A minimum linear least square solution between(i) reconstructed neighboring luma samples or down-sampled samples ofthe reconstructed neighboring luma samples and (ii) reconstructedneighboring chroma samples can be applied to derive the parameters a andb below.

$\begin{matrix}{a = \frac{\begin{matrix}{{N*{\sum}_{i = 1}^{N}( {{Rec\_ C}(i)*{Rec\_ L}^{\prime}(i)} )} -} \\{{\sum}_{i = 1}^{N}{Rec\_ C}(i)*{\sum}_{i = 1}^{N}{Rec\_ L}^{\prime}(i)}\end{matrix}}{\begin{matrix}{{N*{\sum}_{i = 1}^{N}( {{Rec\_ L}^{\prime}(i)*{Rec\_ L}^{\prime}(i)} )} -} \\{{\sum}_{i = 1}^{N}{Rec\_ L}^{\prime}(i)*{\sum}_{i = 1}^{N}{Rec\_ L}^{\prime}(i)}\end{matrix}}} & {{Eq}.5}\end{matrix}$ $\begin{matrix}{b = \frac{{\sum}_{i = 1}^{N}( {{{Rec\_ C}(i)} - {a*{\sum}_{i = 1}^{N}{Rec\_ L}^{\prime}(i)}} }{N}} & {{Eq}.6}\end{matrix}$

In Eqs. 5-6, N reconstructed neighboring chroma samples Rec_C(i) and Ncorresponding luma samples Rec_L′(i) are used. In an example, such aswhen the color format is 4:4:4, the N corresponding luma samplesRec_L′(i) includes N reconstructed neighboring luma samples of the lumablock. In an example, such as when the color format is 4:2:0, the Ncorresponding luma samples Rec_L′(i) includes N down-sampled samples ofthe reconstructed neighboring luma samples of the luma block. i can bean integer from 1 to N.

The N reconstructed neighboring chroma samples used to determine theparameters a and b can include any suitable already reconstructedneighboring samples of the chroma block. The reconstructed neighboringluma samples used to determine the parameters a and b can include anysuitable already reconstructed neighboring samples of the collocatedluma block.

The prediction process of the CCLM mode can include: (1) down-samplingthe collocated luma block and the reconstructed neighboring luma samplesof the collocated luma block to obtain Rec_L′ and the down-sampledneighboring luma samples and thus match a size of the correspondingchroma block, (2) deriving the parameters a and b based on thedown-sampled neighboring luma samples and the reconstructed neighboringchroma samples, for example, using Eqs. 5-6, and (3) applying the CCLMmodel (e.g., Eq. 4) to generate the chroma prediction block Pred_C. Insome examples, step (1) is omitted when the spatial resolutions of thecollocated luma block and the chroma block are identical and step (2) isbased on the reconstructed neighboring luma samples.

FIG. 10 shows examples of reconstructed neighboring luma samples andreconstructed neighboring chroma samples used in the CCLM derivation. Achroma block (1000) is under reconstruction. A width and a height of thechroma block (1000) are M (e.g., 8) and N (e.g., 4), respectively. N andM can be positive integers. A luma block (e.g., a collocated luma block)(1001) that is collocated with the chroma block (1000) is used topredict the chroma block (1000). The luma block (1001) includes lumasamples (1040). The luma block (1001) can have any suitable width andany suitable height. In the example shown in FIG. 10 , the width and theheight of the luma block (1001) are 2M (e.g., 16) and 2N (e.g., 8),respectively.

Neighboring chroma samples (1010) (e.g., shaded in gray) of the chromablock (1000) are already reconstructed. Neighboring luma samples (1020)of the luma block (1001) are already reconstructed. The neighboringchroma samples (1010) can include top neighboring chroma samples (1011)and left neighboring chroma samples (1012). The neighboring luma samples(1020) of the luma block (1001) can include top neighboring luma samples(1021) and left neighboring luma samples (1022).

In the example of FIG. 10 , the neighboring luma samples (1020) aresub-sampled or down-sampled to generate down-sampled neighboring lumasamples (1030) (e.g., shaded in gray) to match a number (e.g., 12) ofthe neighboring chroma samples. In the example shown in FIG. 10 , theneighboring chroma samples (1010) and the down-sampled neighboring lumasamples (1030) can be used to determine parameters a and b, such asshown in Eqs. 5-6.

In an example, the neighboring chroma samples of the chroma block (1000)only include the top neighboring chroma samples (1011) and does notinclude the left neighboring chroma samples (1012). Accordingly, theneighboring luma samples of the luma block (1001) only include the topneighboring luma samples (1021) and does not include the leftneighboring luma samples (1022). As described above, the top neighboringluma samples (1021) can be down-sampled (e.g., the down-sampled lumasamples are shaded in gray) to match a number (e.g., 8) of the topneighboring chroma samples (1011).

In an example, the neighboring chroma samples of the chroma block (1000)only include the left neighboring chroma samples (1012) and does notinclude the top neighboring chroma samples (1011). Accordingly, theneighboring luma samples of the luma block (1001) only include the leftneighboring luma samples (1022) and does not include the top neighboringluma samples (1021). As described above, the left neighboring lumasamples (1022) can be down-sampled (e.g., the down-sampled luma samplesare shaded in gray) to match a number (e.g., 4) of the left neighboringchroma samples (1012).

In some examples, chroma samples in neighboring reconstructed blocks ofthe chroma block (1000) and corresponding luma samples in neighboringreconstructed blocks of the luma block (1001) can be used to determinethe parameters a and b.

The chroma block (1000) can be a Cb block in a Cb channel or a Cr blockin a Cr channel. In an example, for each chroma channel (e.g., Cr orCb), the parameters a and b can be determined separately. For example,the parameters a and b of the Cr block are determined based on chromareconstructed neighboring samples of the Cr block, and the parameters aand b of the Cb block are determined based on chroma reconstructedneighboring samples of the Cb block.

FIG. 10 shows examples of the reconstructed neighboring luma samples andthe reconstructed neighboring chroma samples used in the CCLM derivationfor the chroma block (1000) that has a rectangular shape. The examplesin FIG. 10 can be adapted to a chroma block and a collocated luma blockthat have any shape, such as a square shape. FIG. 11 shows examples ofreconstructed neighboring luma samples (1120) and reconstructedneighboring chroma samples (1110) used in the CCLM derivation for achroma block (1100). A width and a height of the chroma block (1100) areW1 (e.g., 8) and H1 (e.g., 8), respectively where W1 is equal to H1. Aluma block (e.g., a collocated luma block) (1101) that is collocatedwith the chroma block (1100) is used to predict the chroma block (1100).A width and a height of the luma block (1101) are 2W1 (e.g., 16) and 2H1(e.g., 16), respectively.

In some embodiments, the reference samples used to generate the linearmodel parameters a and b are noisy and/or less representative of acontent inside an actual prediction block. Thus, the prediction may besuboptimal with respect to coding efficiency. Accordingly, it may bebeneficial to develop more content adaptive linear models for chromasample prediction, for example.

The disclosure describes an adaptive parameter selection forcross-component prediction in image and video compression. In anembodiment, the slope parameter and/or the offset parameter (e.g., theparameters a and/or the parameter b) used in the CCLM prediction areadaptively adjusted, and thus the linear model can be more contentadaptive for the chroma sample prediction. For example, the linear model(e.g., the parameters a and/or the parameter b) is more adaptive to acontent of the collocated luma block. In an example, a content of thechroma block is related to the content of the collocated luma block, andthus the CCLM prediction can be adaptive to the content of the chromablock.

Adjustments to the slope parameter and/or the offset parameter canmodify the linear function (e.g., Eq. 4) which maps luma sample valuesto chroma sample values such that the chroma sample values can be mappedfrom the luma sample values according to the property of luma samplevalues in the collocated luma block.

As described above, in the CCLM, a model with two parameters (e.g., theparameters a and b in Eq. 4) is used to map luma values to chromavalues. The slope parameter a and the offset parameter b are used in Eq.4. An adjustment of the parameters a and b (e.g., the slope parameterand the offset parameter) can be employed to update the linear model inEq. 4 to an updated linear model in Eq. 7.

Pred_C(x,y)=a′×Rec_L′(x,y)+b′  Eq. 7

In Eq. 7, an updated slope parameter a′ is a function of the slopeparameter a, for example, a′=f1(a), an updated offset parameter b′ is afunction of the offset parameter b, for example, b′=f2(b). Theadjustment to the parameters a and b can be based on local sampleinformation, e.g., local luma reconstructed sample information of thecollocated luma block.

FIGS. 12A-12B show examples of parameter adjustments used in the CCLM.FIG. 12A shows the CCLM with Eq. 4. A predicted chroma sample value(e.g., Cb for a Cb block or Cr for a Cr block) has a linear relationship(1201) corresponding to Eq. 4 with a corresponding luma value (e.g., Y),where the slope of the linear relationship (1201) is the slope parametera and the offset of the linear relationship (1201) is the offsetparameter b. FIG. 12B shows two linear relationships (1201)-(1202)corresponding to Eqs. 4 and 7, respectively. In the linear relationship(1202) corresponding to Eq. 7, a predicted chroma sample value (e.g., Cbfor a Cb block or Cr for a Cr block) has the linear relationship (1202)with a corresponding luma value (e.g., Y) where the slope is the updatedslope parameter a′ and the offset is the updated offset parameter b′.

In the example shown in FIG. 12B, the updated slope parameter a′ is alinear function of the slope parameter a where a′ is (a+u). Anadjustment parameter u used to adjust the slope parameter a can bereferred to as the slope adjustment parameter “u”. The updated offsetparameter b′ can be a linear function of the offset parameter b. In anexample, b′=b−u×y_(r). An adjustment parameter y_(r) used to adjust theoffset parameter b can be referred to as the offset adjustment parameter“y_(r)”. Referring to FIG. 12B, with the adjustments (e.g., a′=a+u andb′=b−u×y_(r)), the linear relationship (1201) (e.g., the mappingfunction used in Eq. 4) is tilted or rotated around a point (1203) togenerate the linear relationship (1202). In an example, the adjustmentparameter y_(r) represents a luminance value (e.g., Y being y_(r)) atthe point (1203) where the linear relationships (1201)-(1202) intercept.

In an example, the slope parameter and the offset parameter areadjusted. In an example, one of the slope parameter and the offsetparameter is adjusted. In some examples, the adjustment parameters u andy_(r) are determined or derived. In some examples, one of the adjustmentparameters u and y_(r) is determined.

In the adjustment formula of a′ (e.g., a′=a+u) and b′ (e.g.,b′=b−u×y_(r)), the adjustment parameter u can be signaled or derived. Avalue of the adjustment parameter u can be either positive or negative.The adjustment parameter y_(r) used to adjust the offset parameter bsuch as in b′=b−u×y_(r) can be determined based on the collocated lumablock. For example, the adjustment parameter y_(r) is determined basedon selected value(s) of respective reference luma sample(s) in thecollocated luma block.

In the CCLM, Eq. 7 can be used to predict a chroma block (e.g., thechroma block (1000)) based on a collocated luma block (e.g., the lumablock (1001)). As described above, the updated offset parameter b′ canbe a linear function of the offset parameter b, such as b′ being(b−u×y_(r)). According to an embodiment of the disclosure, theadjustment parameter y_(r) used to adjust the offset parameter b can bedetermined based on a subset of luma samples in the collocated lumablock (e.g., the luma block (1001)). In an embodiment, the subset ofluma samples in the collocated luma block (e.g., the luma block (1001))does not include one or more samples in the collocated luma block.

FIG. 13 shows examples of sample positions of selected luma samples in acollocated luma block (1300) that can be used to determine theadjustment parameter y_(r). The collocated luma block (1300) iscollocated with a chroma block to be coded (e.g., to be reconstructed).The collocated luma block (1300) includes luma samples (e.g., referenceluma samples) that are already reconstructed. The collocated luma block(1300) or a down-sampled luma block that is down-sampled from thecollocated luma block (1300) can be used as Rec_L′ in Eq. 7 to predictthe chroma block. Further, one or more of the selected luma samples inthe collocated luma block (1300) can be used to determine the adjustmentparameter y_(r).

The luma samples in the collocated luma block (1300) can include lumasamples (e.g., the selected luma samples) (1301)-(1309). The lumasamples (1301)-(1309) are located at a top-left corner, an above center,a top-right corner, a left-most center, a center, a right-most center, abottom-left corner, a bottom center, and a bottom-right corner of thecollocated luma block (1300), respectively.

The adjustment parameter y_(r) can be selected as a sample value of oneof the luma samples (1301)-(1309). The adjustment parameter y_(r) can beselected as an average (e.g., a weighted average) of sample values of aplurality of samples in the luma samples (1301)-(1309).

In an embodiment, the adjustment parameter y_(r) is selected as a samplevalue of the luma sample (1309) at the bottom-right corner of thecollocated luma block (1300).

In an embodiment, the adjustment parameter y_(r) is selected as a samplevalue of the luma sample (1305) at the center of the collocated lumablock (1300).

In an embodiment, the adjustment parameter y_(r) is selected as a samplevalue of the luma sample (1306) at the right-most center of thecollocated luma block (1300).

In an embodiment, the adjustment parameter y_(r) is selected as a samplevalue of the luma sample (1308) at the bottom center of the collocatedluma block (1300).

In an embodiment, the adjustment parameter y_(r) is selected as a samplevalue from a position such as the top-left corner (e.g., correspondingto the luma sample (1301)), the top-right corner (e.g., corresponding tothe luma sample (1303)), or the bottom-left corner (e.g., correspondingto the luma sample (1307)) of the collocated luma block (1300).

In an embodiment, the adjustment parameter y_(r) is determined as anaverage (e.g., a weighted average) of samples values of certain lumasamples, such as the luma samples (1301), (1303), (1307), and (1309)located at the four corners (e.g., the top-left corner, the top-rightcorner, the bottom-left corner, and the bottom-right corner) of thecollocated luma block (1300).

In an embodiment, the adjustment parameter y_(r) is determined as anaverage (e.g., a weighted average) of sample values of a plurality ofsamples in the luma samples (1301)-(1309) in the collocated luma block(1300).

The luma samples (1301)-(1309) are examples of luma samples in thecollocated luma block (1300) that can be used to determine theadjustment parameter y_(r). Another luma sample or other luma samples inthe collocated luma block (1300) that are not in the luma samples(1301)-(1309) can be used to determine the adjustment parameter y_(r).

Selection of luma sample(s) in a collocated luma block to adjust theparameters a and b used in the CCLM model can be made more adaptive fordifferent chroma blocks or different regions (e.g., subblocks) inside achroma block where the collocated luma block is collocated with thechroma block.

In an embodiment, different adjustment parameters y_(r) are used fordifferent chroma blocks. For example, luma samples located at differentlocations in respective luma blocks can be used as the adjustmentparameters y_(r) of the different chroma blocks. For a chroma block,such as the chroma block collocated with the collocated luma block(1300) in FIG. 13 , one of the available options, such as one of theluma samples (1301)-(1309), can be used for the chroma block. In anexample, one of (i) the luma sample (1305) at the center position of thecollocated luma block (1300) and (ii) the luma sample (1309) at thebottom-right corner position of the collocated luma block (1300) can bechosen to determine the adjustment parameters y_(r) used to adjust theoffset parameter b. For the chroma block, a selection indicator, forexample, indicating which sample(s) are used to determine the adjustmentparameters y_(r), can be signaled or derived. The selection indicatorcan be a selection index or a selection flag.

Different chroma blocks can have different methods to obtain adjustmentparameters y_(r). In an example, a selection index for a first chromablock indicates that an adjustment parameter y_(r) of the first chromablock is determined based on a luma sample at a center position of afirst luma block that is collocated with the first chroma block. Thus,the adjustment parameter y_(r) of the first chroma block is determinedbased on the luma sample at the center position of the first luma block.A selection index for a second chroma block indicates that an adjustmentparameter y_(r) of the second chroma block is determined based on a lumasample at a right-most center position of a second luma block that iscollocated with the second chroma block. Thus, the adjustment parametery_(r) of the second chroma block is determined based on the luma sampleat the right-most center position of the second luma block.

In an embodiment, adjustment parameters y_(r) of different regions in achroma block can be determined using different sample values in acollocated luma block. FIG. 14 shows an example of a chroma block (1410)and a collocated luma block (1400) that is collocated with the chromablock (1410). The chroma block (1410) can be predicted based on thecollocated luma block (1400), for example, when a spatial resolution ofthe chroma block (1410) is identical to a spatial resolution of thecollocated luma block (1400) (e.g., a color format is 4:4:4). The chromablock (1410) can be predicted based on a down-sampled luma block that isdown-sampled from the collocated luma block (1400), for example, whenthe spatial resolution of the chroma block (1410) is different from thespatial resolution of the collocated luma block (1400).

The chroma block (1410) includes multiple regions (also referred to asmultiple chroma regions), such as a top-left quarter region (1411), atop-right quarter region (1412), a bottom-left quarter region (1413),and a bottom-right quarter region (1414). An adjustment parameter y_(r)of each of the multiple regions in the chroma block (1410) can bedetermined based on a respective sample in the collocated luma block(1400).

For example, a center position (1401) of the collocated luma block(1400) is used to determine an adjustment parameter y_(r) of thetop-left quarter region (1411) of the chroma block (1410); a right-mostcenter position (1402) of the collocated luma block (1400) is used todetermine an adjustment parameter y_(r) of the top-right quarter region(1412) of the chroma block (1410); a bottom center position (1403) ofthe collocated luma block (1400) is used to determine an adjustmentparameter y_(r) of the bottom-left quarter region (1413) of the chromablock (1410); a bottom-right corner position (1404) of the collocatedluma block (1400) is used to determine an adjustment parameter y_(r) ofthe bottom-right quarter region (1414) of the chroma block (1410).

In an embodiment, an adjustment parameter y_(r) of one of the multipleregions in the chroma block (1410) is determined based on acorresponding region in the collocated luma block (1400). For example,the corresponding region in the collocated luma block (1400) iscollocated with the one of the multiple regions in the chroma block(1410).

Referring to FIG. 14 , the collocated luma block (1400) includesmultiple regions (also referred to as multiple luma regions) that arecollocated with the multiple chroma regions in the chroma block (1410).For example, the multiple luma regions in the collocated luma block(1400) includes a top-left quarter region (1421), a top-right quarterregion (1422), a bottom-left quarter region (1423), and a bottom-rightquarter region (1424) that are collocated with the top-left quarterregion (1411), the top-right quarter region (1412), the bottom-leftquarter region (1413), and the bottom-right quarter region (1414) in thechroma block, respectively.

In an example, an average of luma sample values of the top-left quarterregion (1421) of the collocated luma block (1400) is used to determinethe adjustment parameter y_(r) of the top-left quarter region (1411) inthe chroma block (1410); an average of luma sample values of thetop-right quarter region (1422) of the collocated luma block (1400) isused to determine the adjustment parameter y_(r) of the top-rightquarter region (1412) in the chroma block (1410); an average of lumasample values of the bottom-left quarter region (1423) of the collocatedluma block (1400) is used to determine the adjustment parameter y_(r) ofthe bottom-left quarter region (1413) in the chroma block (1410); and anaverage of luma sample values of the bottom-right quarter region (1424)of the collocated luma block (1400) is used to determine the adjustmentparameter y_(r) of the bottom-right quarter region (1414) in the chromablock (1410).

In an example, a chroma region (e.g., (1411)) is further divided intomultiple chroma sub-regions and a collocated luma region (e.g., (1421))is further divided into multiple luma sub-regions. An adjustmentparameter y_(r) of each chroma sub-region in the region (1411) can bedetermined based on an average of luma sample values of the respectiveluma sub-region in the region (1421).

FIG. 15 shows an example of a chroma block (1510) and a collocated lumablock (1500) that is collocated with the chroma block (1510). The chromablock (1510) can be predicted based on the collocated luma block (1500)or a down-sampled luma block that is down-sampled from the collocatedluma block (1500), as described in FIG. 14 .

The chroma block (1510) includes multiple chroma regions, such as atop-left quarter region (1511), a top-right quarter region (1512), abottom-left quarter region (1513), and a bottom-right quarter region(1514). An adjustment parameter y_(r) of each chroma region in thechroma block (1510) can be determined based on an average of certainluma sample values, such as the four luma sample values located at fourcorners of a corresponding luma region in the collocated luma block(1500).

The collocated luma block (1500) includes multiple luma regions that arecollocated with the multiple chroma regions in the chroma block (1510).For example, the multiple luma regions in the collocated luma block(1500) includes a top-left quarter region (1521), a top-right quarterregion (1522), a bottom-left quarter region (1523), and a bottom-rightquarter region (1524) that are collocated with the top-left quarterregion (1511), the top-right quarter region (1512), the bottom-leftquarter region (1513), and the bottom-right quarter region (1514) in thechroma block, respectively.

In an example, an average of luma sample values at four corners(1501)-(1504) of the top-left quarter region (1521) of the collocatedluma block (1500) is used to determine the adjustment parameter y_(r) ofthe top-left quarter region (1511) in the chroma block (1510); anaverage of luma sample values at four corners of the top-right quarterregion (1522) of the collocated luma block (1500) is used to determinethe adjustment parameter y_(r) of the top-right quarter region (1512) inthe chroma block (1510); an average of luma sample values at fourcorners of the bottom-left quarter region (1523) of the collocated lumablock (1500) is used to determine the adjustment parameter y_(r) of thebottom-left quarter region (1513) in the chroma block (1510); and anaverage of luma sample values at four corners of the bottom-rightquarter region (1524) of the collocated luma block (1500) is used todetermine the adjustment parameter y_(r) of the bottom-right quarterregion (1514) in the chroma block (1510).

In the descriptions with reference to FIGS. 14-15 , the chroma block(e.g., 1410) includes four regions (e.g., (1411)-(1414)). Thedescriptions in FIGS. 14-15 can be applied to a chroma block when thechroma block includes M number of regions with M being an integer largerthan 1.

Referring back to FIG. 14 , the regions (1411)-(1414) can be subblocksin the chroma block (1410). An indicator associated with the chromablock (1410) can indicate the CCLM mode for the chroma block (1410).Each subblock in the chroma block (1410) can be predicted differentlyusing the embodiments described in FIG. 14 . In an example, a forwardtransform or an inverse transform is applied to the entire chroma block(1410) to transform the entire chroma block (1410). In an example, thechroma block (1410) is partitioned into multiple TBs that are differentfrom the regions (1411)-(1414), and each of the multiple TBs istransformed using a suitable transform.

As described in FIGS. 14-15 , adjustment parameters y_(r) of differentregions (e.g., the regions (1411)-(1414)) in a chroma block (e.g.,(1410)) can be different. In an example, a same offset parameter b, suchas determined using Eq. 6, is used for the different regions, andcorresponding updated offset parameters b′ of the different regions canbe obtained based on the offset parameter b and the respectiveadjustment parameters y_(r) of the different regions. In an example,different offset parameters b can be used for the different regions.

The adjustment parameter u in the adjustment equations (e.g., a′=a+u andb′=b−u×y_(r)) can be derived based on (i) reconstructed neighboring lumasamples (e.g., (1020)) of a collocated luma block (e.g., the luma block(1001)) and (ii) collocated luma samples (e.g., (1040)) in thecollocated luma block (e.g., the luma block (1001)). According to anembodiment of the disclosure, the adjustment parameter u can be derivedbased on differences between (i) the reconstructed neighboring lumasamples and (ii) the collocated luma samples in the collocated lumablock.

In an embodiment, the adjustment parameter u is determined based on adifference between (i) a first average (referred to as Rec_L′(Nei))based on the reconstructed neighboring luma samples of the collocatedluma block and (ii) a second average (referred to as Rec_L′(Col)) basedon the collocated luma samples in the collocated luma block. In anexample, the adjustment parameter u is a linear function of thedifference, such as u=M (Rec_L′(Col) −Rec_L′(Nei))+K, where M and K areconstants. In an example, the adjustment parameter u is a piece-wiselinear function of the difference, where a mapping table is designed tomap a difference of the first average Rec_L′(Nei) and the secondRec_L′(Col)) into a value of the adjustment parameter u.

The first average Rec_L′(Nei) can be an average of a plurality ofsamples in the reconstructed neighboring luma samples of the collocatedluma block. The second average Rec_L′(Col) can be an average of aplurality of samples in the collocated luma samples in the collocatedluma block.

In an example, the first average Rec_L′(Nei) is an average of all thereconstructed neighboring luma samples (e.g., (1020)) of the collocatedluma block (e.g., (1001)). In an example, the second average Rec_L′(Col)is an average of all the collocated luma samples (e.g., (1040)) in thecollocated luma block (e.g., (1001)).

In an embodiment, the reconstructed neighboring luma samples of thecollocated luma block used to calculate the first average Rec_L′(Nei)are the selected neighboring samples Rec_L′(i) that are used incalculating the CCLM parameters a and b, such as used in Eqs. 5-6.Referring to FIG. 10 , the selected neighboring samples Rec_L′(i) caninclude a subset of samples in the reconstructed neighboring lumasamples (1020), such as the left neighboring luma samples (1022), thetop neighboring luma samples (1021), or the like.

In an embodiment, the second average Rec_L′(Col) can be determined basedon a subset of the collocated luma samples selected from the collocatedluma block. Referring to FIG. 13 , one or more of the samples(1301)-(1309) can be used in the selected subset.

In an embodiment, a number of samples used to calculate the secondaverage Rec_L′(Col) is set based on a number of samples used tocalculate the first average Rec_L′(Nei). For example, a number ofsamples used to calculate the second average Rec_L′(Col) is set to beequal to a number of samples used to calculate the first averageRec_L′(Nei).

In some examples, the first average Rec_L′(Nei) is determined based ondown-sampled neighboring samples of the reconstructed neighboring lumasamples of the collocated luma block.

In an example, a same scaling parameter a, such as determined using Eq.5, is used for different regions in a chroma block, and correspondingupdated scaling parameters a′ of the different regions can be obtainedbased on the scaling parameter a and respective adjustment parameters uof the different regions. In an example, different scaling parameters acan be used for the different regions.

FIG. 16 shows a flow chart outlining a process (e.g., an encodingprocess) (1600) according to an embodiment of the disclosure. Theprocess (1600) can be executed by an apparatus for video coding that caninclude processing circuitry. In various embodiments, the process (1600)is executed by the processing circuitry in the apparatus, such as theprocessing circuitry in the terminal devices (310), (320), (330) and(340), processing circuitry that performs functions of a video encoder(e.g., (403), (603), (703)), or the like. In some embodiments, theprocess (1600) is implemented in software instructions, thus when theprocessing circuitry executes the software instructions, the processingcircuitry performs the process (1600). The process starts at (S1601),and proceeds to (S1610).

At (S1610), for a first region in a chroma block to be encoded in acurrent picture using a cross-component linear model (CCLM) mode, afirst adjustment parameter (e.g., y_(r)) used to adjust an offsetparameter (e.g., b) in the CCLM mode can be determined based on a firstsubset of reconstructed samples in a collocated luma block in thecurrent picture. The first subset of the reconstructed samples does notinclude one or more samples in the collocated luma block.

In an example, the first region in the chroma block includes the entirechroma block. The first subset of the reconstructed samples in thecollocated luma block is one sample in the collocated luma block. Thefirst adjustment parameter can be determined to be a sample value of theone sample in the collocated luma block, such as described in FIG. 13 .

In an example, the first region includes the entire chroma block. Thefirst subset of the reconstructed samples includes a plurality ofsamples in the collocated luma block. The first adjustment parameter canbe determined to be an average of sample values of the plurality ofsamples in the collocated luma block, such as described in FIG. 13 .

At (S1620), a first updated offset parameter can be determined based atleast on the offset parameter and the first adjustment parameter.

At (S1630), the first region can be encoded based at least on the firstupdated offset parameter using the CCLM mode. In an example, predictioninformation indicating that the CCLM mode is applied to the chroma blockis encoded.

The encoded first region and the prediction information can be includedin a coded video bitstream and are sent to a decoder.

In an example, the first region includes the entire chroma block. Theprediction information further indicates which of the samples in thecollocated luma block is included in the first subset of thereconstructed samples. In an example, which of the samples in thecollocated luma block is included in the first subset of thereconstructed samples is signaled in the coded video bitstream.

Then, the process proceeds to (S1699) and terminates.

The process (1600) can be suitably adapted to various scenarios andsteps in the process (1600) can be adjusted accordingly. One or more ofthe steps in the process (1600) can be adapted, omitted, repeated,and/or combined. Any suitable order can be used to implement the process(1600). Additional step(s) can be added.

In an example, the chroma block further includes a second region. Thefirst subset of the reconstructed samples is a first sample in thecollocated luma block. For the second region in the chroma block, asecond adjustment parameter used to adjust the offset parameter in theCCLM mode can be determined based on a second sample in the collocatedluma block. The second sample can be different from the first sample. Asecond updated offset parameter can be determined based at least on theoffset parameter and the second adjustment parameter. The second regionin the chroma block can be reconstructed based at least on the secondupdated offset parameter using the CCLM mode.

In an example, the chroma block further includes the second region. Thecollocated luma block includes a first luma region and a second lumaregion that are collocated with the first region and the second region,respectively. The first subset of the reconstructed samples includes aplurality of samples in the first luma region. For the second region inthe chroma block, a second adjustment parameter used to adjust theoffset parameter in the CCLM mode can be determined based on a pluralityof samples in the second luma region. A second updated offset parametercan be determined based at least on the offset parameter and the secondadjustment parameter. The second region in the chroma block can bereconstructed based at least on the second updated offset parameterusing the CCLM mode.

In an example, the chroma block further includes a second region. Thecollocated luma block includes a first luma region and a second lumaregion that are collocated with the first region and the second region,respectively. The first subset of the reconstructed samples includes atop-left sample, a top-right sample, a bottom-left sample, and abottom-right sample in the first luma region. The first adjustmentparameter can be determined to be an average of the top-left sample, thetop-right sample, the bottom-left sample, and the bottom-right sample inthe first luma region. For the second region in the chroma block, asecond adjustment parameter used to adjust the offset parameter in theCCLM mode can be determined to be an average of a top-left sample, atop-right sample, a bottom-left sample, and a bottom-right sample in thesecond luma region. A second updated offset parameter can be determinedbased at least on the second offset parameter and the second adjustmentparameter. The second region in the chroma block can be reconstructedbased at least on the second updated offset parameter using the CCLMmode.

In an example, for the first region, an updated scaling parameter (e.g.,a′) can be determined to be a sum of a scaling parameter (e.g., theparameter a) used in the CCLM mode and an adjustment parameter (e.g.,the adjustment parameter u) used to adjust the scaling parameter. Thefirst updated offset parameter (e.g., b′) can be determined to be(b−u×y_(r)) where b is the offset parameter, u is the adjustmentparameter used to adjust the scaling parameter, and y_(r) is the firstadjustment parameter. The first region in the chroma block can bereconstructed based on the first updated offset parameter and theupdated scaling parameter using the CCLM mode.

In an embodiment, for the first region, the adjustment parameter (e.g.,u) used to adjust the scaling parameter (e.g., a) is determined based on(i) reconstructed luma samples in one or more neighboring luma blocks ofthe collocated luma block and (ii) samples in the collocated luma block.In an example, for the first region, the adjustment parameter used toadjust the scaling parameter can be determined based on a differencebetween an average of the reconstructed luma samples in the one or moreneighboring luma blocks and an average of the samples in the collocatedluma block.

FIG. 17 shows a flow chart outlining a process (e.g., a decodingprocess) (1700) according to an embodiment of the disclosure. Theprocess (1700) can be used in a video decoder. The process (1700) can beexecuted by an apparatus for video coding that can include receivingcircuitry and processing circuitry. The processing circuitry in theapparatus, such as the processing circuitry in the terminal devices(310), (320), (330) and (340), the processing circuitry that performsfunctions of the video decoder (410), the processing circuitry thatperforms functions of the video decoder (510), and the like can beconfigured to perform the process (1700). In some examples, the process(1700) is used in a video encoder (e.g., the video encoder (403), thevideo encoder (603)). In an example, the process (1700) is executed byprocessing circuitry that performs functions of an video encoder (e.g.,the video encoder (403), the video encoder (603)). In some embodiments,the process (1700) is implemented in software instructions, thus whenthe processing circuitry executes the software instructions, theprocessing circuitry performs the process (1700). The process starts at(S1701) and proceeds to (S1710).

At (S1710), prediction information of a chroma block to be reconstructedin a current picture can be decoded. The prediction information canindicate that a cross-component linear model (CCLM) mode is applied tothe chroma block.

At (S1720), for a first region in the chroma block, a first adjustmentparameter (also referred to as a first adjustment value) (e.g., y_(r))used to adjust (or modify) an offset parameter (e.g., b) in the CCLMmode can be determined based on a first subset of samples (orreconstructed samples) in a collocated luma block in the currentpicture. The collocated luma block is a luma block that is collocatedwith the chroma block. The first subset of samples does not include oneor more samples in the collocated luma block. In an example, the samplesin the collocated luma block are already reconstructed.

In an example, the first region in the chroma block includes the entirechroma block. The first subset of samples in the collocated luma blockis one sample in the collocated luma block. The first adjustmentparameter can be determined to be a sample value of the one sample inthe collocated luma block, such as described in FIG. 13 .

In an example, the first region includes the entire chroma block. Thefirst subset of samples includes a plurality of samples in thecollocated luma block. The first adjustment parameter can be determinedto be an average of sample values of the plurality of samples in thecollocated luma block, such as described in FIG. 13 .

In an example, the first region includes the entire chroma block. Theprediction information further indicates which of the samples in thecollocated luma block is included in the first subset of samples. In anexample, which of the samples in the collocated luma block is includedin the first subset of samples is signaled in the coded video bitstream.In an example, which of the samples in the collocated luma block isincluded in the first subset of samples is derived.

At (S1730), for the first region in the chroma block, a first updatedoffset parameter (e.g., b′) can be determined based at least on theoffset parameter (e.g., b) and the first adjustment parameter (e.g.,y_(r)), such as b′=b−u×y_(r) as described above.

At (S1740), the first region in the chroma block can be reconstructedbased at least on the first updated offset parameter using the CCLMmode. Then, the process proceeds to (S1799) and terminates.

The process (1700) can be suitably adapted to various scenarios andsteps in the process (1700) can be adjusted accordingly. One or more ofthe steps in the process (1700) can be adapted, omitted, repeated,and/or combined. Any suitable order can be used to implement the process(1700). Additional step(s) can be added.

In an example, the chroma block further includes a second region. Thefirst subset of samples is a first sample in the collocated luma block.For the second region in the chroma block, a second adjustment parameterused to adjust the offset parameter in the CCLM mode can be determinedbased on a second sample in the collocated luma block. The second samplecan be different from the first sample. A second updated offsetparameter can be determined based at least on the offset parameter andthe second adjustment parameter. The second region in the chroma blockcan be reconstructed based at least on the second updated offsetparameter using the CCLM mode.

In an example, the chroma block further includes the second region. Thecollocated luma block includes a first luma region and a second lumaregion that are collocated with the first region and the second region,respectively. The first subset of samples includes a plurality ofsamples in the first luma region. For the second region in the chromablock, a second adjustment parameter used to adjust the offset parameterin the CCLM mode can be determined based on a plurality of samples inthe second luma region. A second updated offset parameter can bedetermined based at least on the offset parameter and the secondadjustment parameter. The second region in the chroma block can bereconstructed based at least on the second updated offset parameterusing the CCLM mode.

In an example, the chroma block further includes a second region. Thecollocated luma block includes a first luma region and a second lumaregion that are collocated with the first region and the second region,respectively. The first subset of samples includes a top-left sample, atop-right sample, a bottom-left sample, and a bottom-right sample in thefirst luma region. The first adjustment parameter can be determined tobe an average of the top-left sample, the top-right sample, thebottom-left sample, and the bottom-right sample in the first lumaregion. For the second region in the chroma block, a second adjustmentparameter used to adjust the offset parameter in the CCLM mode can bedetermined to be an average of a top-left sample, a top-right sample, abottom-left sample, and a bottom-right sample in the second luma region.A second updated offset parameter can be determined based at least onthe second offset parameter and the second adjustment parameter. Thesecond region in the chroma block can be reconstructed based at least onthe second updated offset parameter using the CCLM mode.

In an example, for the first region, an updated scaling parameter (e.g.,a′) can be determined to be a sum of a scaling parameter (also referredto as a slope parameter) (e.g., the parameter a) used in the CCLM modeand an adjustment parameter (also referred to as an adjustment value)(e.g., the adjustment parameter u) used to adjust the scaling parameter.The first updated offset parameter (e.g., b′) can be determined to be(b−u×y_(r)) where b is the offset parameter, u is the adjustmentparameter used to adjust the scaling parameter, and y_(r) is the firstadjustment parameter. The first region in the chroma block can bereconstructed based on the first updated offset parameter and theupdated scaling parameter using the CCLM mode.

In an embodiment, for the first region, the adjustment parameter (e.g.,u) used to adjust the scaling parameter (e.g., a) is determined based on(i) reconstructed luma samples in one or more neighboring luma blocks ofthe collocated luma block and (ii) samples in the collocated luma block.In an example, for the first region, the adjustment parameter used toadjust the scaling parameter can be determined based on a differencebetween an average of the reconstructed luma samples in the one or moreneighboring luma blocks and an average of the samples in the collocatedluma block.

In an embodiment, for a first region in the chroma block, a firstadjustment value used to modify an offset parameter in the CCLM mode isdetermined based on a first subset of reconstructed samples in a lumablock that is collocated with the chroma block in the current picture.The first subset of the reconstructed samples does not include one ormore samples in the luma block. The offset parameter can be updatedbased at least on the first adjustment value. A second adjustment valueused to modify a slope parameter in the CCLM mode can be determinedbased on a second subset of the reconstructed samples in the luma blockand updates the slope parameter based at least on the second adjustmentvalue. The first region in the chroma block can be reconstructed basedat least on the updated offset parameter and the updated slope parameterusing the CCLM mode.

In an example, the second subset of the reconstructed samples includesthe first subset of the reconstructed samples.

In an example, the second adjustment value is determined based on thereconstructed samples in the entire luma block.

Embodiments in the disclosure may be used separately or combined in anyorder. Further, each of the methods (or embodiments), an encoder, and adecoder may be implemented by processing circuitry (e.g., one or moreprocessors or one or more integrated circuits). In one example, the oneor more processors execute a program that is stored in a non-transitorycomputer-readable medium.

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media. For example, FIG. 18 shows a computersystem (1800) suitable for implementing certain embodiments of thedisclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by one or more computer central processingunits (CPUs), Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 18 for computer system (1800) are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system (1800).

Computer system (1800) may include certain human interface inputdevices. Such a human interface input device may be responsive to inputby one or more human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard (1801), mouse (1802), trackpad (1803), touchscreen (1810), data-glove (not shown), joystick (1805), microphone(1806), scanner (1807), camera (1808).

Computer system (1800) may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen (1810), data-glove (not shown), or joystick (1805), butthere can also be tactile feedback devices that do not serve as inputdevices), audio output devices (such as: speakers (1809), headphones(not depicted)), visual output devices (such as screens (1810) toinclude CRT screens, LCD screens, plasma screens, OLED screens, eachwith or without touch-screen input capability, each with or withouttactile feedback capability—some of which may be capable to output twodimensional visual output or more than three dimensional output throughmeans such as stereographic output; virtual-reality glasses (notdepicted), holographic displays and smoke tanks (not depicted)), andprinters (not depicted).

Computer system (1800) can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW(1820) with CD/DVD or the like media (1821), thumb-drive (1822),removable hard drive or solid state drive (1823), legacy magnetic mediasuch as tape and floppy disc (not depicted), specialized ROM/ASIC/PLDbased devices such as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system (1800) can also include an interface (1854) to one ormore communication networks (1855). Networks can for example bewireless, wireline, optical. Networks can further be local, wide-area,metropolitan, vehicular and industrial, real-time, delay-tolerant, andso on. Examples of networks include local area networks such asEthernet, wireless LANs, cellular networks to include GSM, 3G, 4G, 5G,LTE and the like, TV wireline or wireless wide area digital networks toinclude cable TV, satellite TV, and terrestrial broadcast TV, vehicularand industrial to include CANBus, and so forth. Certain networkscommonly require external network interface adapters that attached tocertain general purpose data ports or peripheral buses (1849) (such as,for example USB ports of the computer system (1800)); others arecommonly integrated into the core of the computer system (1800) byattachment to a system bus as described below (for example Ethernetinterface into a PC computer system or cellular network interface into asmartphone computer system). Using any of these networks, computersystem (1800) can communicate with other entities. Such communicationcan be uni-directional, receive only (for example, broadcast TV),uni-directional send-only (for example CANbus to certain CANbusdevices), or bi-directional, for example to other computer systems usinglocal or wide area digital networks. Certain protocols and protocolstacks can be used on each of those networks and network interfaces asdescribed above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core (1840) of thecomputer system (1800).

The core (1840) can include one or more Central Processing Units (CPU)(1841), Graphics Processing Units (GPU) (1842), specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)(1843), hardware accelerators for certain tasks (1844), graphicsadapters (1850), and so forth. These devices, along with Read-onlymemory (ROM) (1845), Random-access memory (1846), internal mass storagesuch as internal non-user accessible hard drives, SSDs, and the like(1847), may be connected through a system bus (1848). In some computersystems, the system bus (1848) can be accessible in the form of one ormore physical plugs to enable extensions by additional CPUs, GPU, andthe like. The peripheral devices can be attached either directly to thecore's system bus (1848), or through a peripheral bus (1849). In anexample, the screen (1810) can be connected to the graphics adapter(1850). Architectures for a peripheral bus include PCI, USB, and thelike.

CPUs (1841), GPUs (1842), FPGAs (1843), and accelerators (1844) canexecute certain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM(1845) or RAM (1846). Transitional data can be also be stored in RAM(1846), whereas permanent data can be stored for example, in theinternal mass storage (1847). Fast storage and retrieve to any of thememory devices can be enabled through the use of cache memory, that canbe closely associated with one or more CPU (1841), GPU (1842), massstorage (1847), ROM (1845), RAM (1846), and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture (1800), and specifically the core (1840) can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core (1840) that are of non-transitorynature, such as core-internal mass storage (1847) or ROM (1845). Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core (1840). Acomputer-readable medium can include one or more memory devices orchips, according to particular needs. The software can cause the core(1840) and specifically the processors therein (including CPU, GPU,FPGA, and the like) to execute particular processes or particular partsof particular processes described herein, including defining datastructures stored in RAM (1846) and modifying such data structuresaccording to the processes defined by the software. In addition or as analternative, the computer system can provide functionality as a resultof logic hardwired or otherwise embodied in a circuit (for example:accelerator (1844)), which can operate in place of or together withsoftware to execute particular processes or particular parts ofparticular processes described herein. Reference to software canencompass logic, and vice versa, where appropriate. Reference to acomputer-readable media can encompass a circuit (such as an integratedcircuit (IC)) storing software for execution, a circuit embodying logicfor execution, or both, where appropriate. The present disclosureencompasses any suitable combination of hardware and software.

Appendix A: Acronyms

-   JEM: joint exploration model-   VVC: versatile video coding-   BMS: benchmark set-   MV: Motion Vector-   HEVC: High Efficiency Video Coding-   SEI: Supplementary Enhancement Information-   VUI: Video Usability Information-   GOPs: Groups of Pictures-   TUs: Transform Units,-   PUs: Prediction Units-   CTUs: Coding Tree Units-   CTBs: Coding Tree Blocks-   PBs: Prediction Blocks-   HRD: Hypothetical Reference Decoder-   SNR: Signal Noise Ratio-   CPUs: Central Processing Units-   GPUs: Graphics Processing Units-   CRT: Cathode Ray Tube-   LCD: Liquid-Crystal Display-   OLED: Organic Light-Emitting Diode-   CD: Compact Disc-   DVD: Digital Video Disc-   ROM: Read-Only Memory-   RAM: Random Access Memory-   ASIC: Application-Specific Integrated Circuit-   PLD: Programmable Logic Device-   LAN: Local Area Network-   GSM: Global System for Mobile communications-   LTE: Long-Term Evolution-   CANBus: Controller Area Network Bus-   USB: Universal Serial Bus-   PCI: Peripheral Component Interconnect-   FPGA: Field Programmable Gate Areas-   SSD: solid-state drive-   IC: Integrated Circuit-   CU: Coding Unit-   CCLM: cross-component linear model

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

What is claimed is:
 1. A method of video processing in a decoder,comprising: decoding prediction information of a chroma block to bereconstructed in a current picture, the prediction informationindicating that a cross-component linear model (CCLM) mode is applied tothe chroma block; and for a first region in the chroma block,determining a first adjustment value used to modify an offset parameterin the CCLM mode based on a first subset of reconstructed samples in aluma block that is collocated with the chroma block in the currentpicture, the first subset of the reconstructed samples not including oneor more samples in the luma block; updating the offset parameter basedat least on the first adjustment value; determining a second adjustmentvalue used to modify a slope parameter in the CCLM mode based on asecond subset of the reconstructed samples in the luma block; updatingthe slope parameter based at least on the second adjustment value; andreconstructing the first region in the chroma block based at least onthe updated offset parameter and the updated slope parameter using theCCLM mode.
 2. The method of claim 1, wherein the first region in thechroma block includes the entire chroma block; the first subset of thereconstructed samples in the luma block is one reconstructed sample inthe luma block; and the determining the first adjustment value includesdetermining the first adjustment value to be a sample value of the onereconstructed sample in the luma block.
 3. The method of claim 1,wherein the first region includes the entire chroma block; the firstsubset of the reconstructed samples includes a plurality ofreconstructed samples in the luma block, and the determining the firstadjustment value includes determining the first adjustment value to bean average of sample values of the plurality of reconstructed samples inthe luma block.
 4. The method of claim 1, wherein the first regionincludes the entire chroma block; and the prediction information furtherindicates which of the reconstructed samples in the luma block isincluded in the first subset of the reconstructed samples.
 5. The methodof claim 1, wherein the chroma block further includes a second region;the first subset of the reconstructed samples is a first reconstructedsample in the luma block, and for the second region in the chroma block,determining a second adjustment parameter used to adjust the offsetparameter in the CCLM mode based on a second sample in the luma block,the second sample being different from the first sample; determining asecond updated offset parameter based at least on the offset parameterand the second adjustment parameter; and reconstructing the secondregion in the chroma block based at least on the second updated offsetparameter using the CCLM mode.
 6. The method of claim 1, wherein thechroma block further includes a second region; the luma block includes afirst luma region and a second luma region that are collocated with thefirst region and the second region, respectively; the first subset ofthe reconstructed samples includes a plurality of samples in the firstluma region; and for the second region in the chroma block, determininga second adjustment parameter used to adjust the offset parameter in theCCLM mode based on a plurality of samples in the second luma region;determining a second updated offset parameter based at least on theoffset parameter and the second adjustment parameter; and reconstructingthe second region in the chroma block based at least on the secondupdated offset parameter using the CCLM mode.
 7. The method of claim 1,wherein the chroma block further includes a second region; the lumablock includes a first luma region and a second luma region that arecollocated with the first region and the second region, respectively;the first subset of the reconstructed samples includes a top-leftsample, a top-right sample, a bottom-left sample, and a bottom-rightsample in the first luma region; the determining the first adjustmentvalue includes determining the first adjustment value to be an averageof the top-left sample, the top-right sample, the bottom-left sample,and the bottom-right sample in the first luma region; and for the secondregion in the chroma block, determining a second adjustment parameterused to adjust the offset parameter in the CCLM mode to be an average ofa top-left sample, a top-right sample, a bottom-left sample, and abottom-right sample in the second luma region; determining a secondupdated offset parameter based at least on the second offset parameterand the second adjustment parameter; and reconstructing the secondregion in the chroma block based at least on the second updated offsetparameter using the CCLM mode.
 8. The method of claim 1, wherein thedetermining the updated offset parameter includes determining theupdated offset parameter to be (b−u×y_(r)), b being the offsetparameter, u being the second adjustment value used to modify the slopeparameter, y_(r) being the first adjustment value; and thereconstructing the first region includes reconstructing the first regionin the chroma block based on the updated offset parameter and theupdated slope parameter using the CCLM mode.
 9. The method of claim 8,further comprising: for the first region, determining the secondadjustment value used to modify the slope parameter based on (i)reconstructed luma samples in one or more neighboring luma blocks of theluma block and (ii) the second subset of the reconstructed samples inthe luma block.
 10. The method of claim 9, wherein the determining thesecond adjustment value used to modify the slope parameter comprises:for the first region, determining the second adjustment value used tomodify the slope parameter based on a difference between an average ofthe reconstructed luma samples in the one or more neighboring lumablocks and an average of the second subset of the reconstructed samplesin the luma block.
 11. The method of claim 1, wherein the second subsetof the reconstructed samples includes the first subset of thereconstructed samples.
 12. The method of claim 1, wherein thedetermining the second adjustment value comprises: determining thesecond adjustment value based on the reconstructed samples in the entireluma block.
 13. An apparatus for video decoding, comprising: processingcircuitry configured to: decode prediction information of a chroma blockto be reconstructed in a current picture, the prediction informationindicating that a cross-component linear model (CCLM) mode is applied tothe chroma block; and for a first region in the chroma block, determinea first adjustment value used to adjust an offset parameter in the CCLMmode based on a first subset of reconstructed samples in a luma blockthat is collocated with the chroma block in the current picture, thefirst subset of the reconstructed samples not including one or moresamples in the luma block; update the offset parameter based at least onthe first adjustment value; determining a second adjustment value usedto modify a slope parameter in the CCLM mode based on a second subset ofthe reconstructed samples in the luma block; updating the slopeparameter based at least on the second adjustment value; and reconstructthe first region in the chroma block based at least on the updatedoffset parameter using the CCLM mode.
 14. The apparatus of claim 13,wherein the first region in the chroma block includes the entire chromablock; the first subset of the reconstructed samples in the luma blockis one reconstructed sample in the luma block; and the processingcircuitry is configured to determine the first adjustment value to be asample value of the one reconstructed sample in the luma block.
 15. Theapparatus of claim 13, wherein the first region includes the entirechroma block; the first subset of the reconstructed samples includes aplurality of reconstructed samples in the luma block, and the processingcircuitry is configured to determine the first adjustment value to be anaverage of sample values of the plurality of reconstructed samples inthe luma block.
 16. The apparatus of claim 13, wherein the first regionincludes the entire chroma block; and the prediction information furtherindicates which of the reconstructed samples in the luma block isincluded in the first subset of the reconstructed samples.
 17. Theapparatus of claim 13, wherein the chroma block further includes asecond region; the first subset of the reconstructed samples is a firstreconstructed sample in the luma block, and for the second region in thechroma block, the processing circuitry is configured to: determine asecond adjustment parameter used to adjust the offset parameter in theCCLM mode based on a second sample in the luma block, the second samplebeing different from the first sample; determine a second updated offsetparameter based at least on the offset parameter and the secondadjustment parameter; and reconstruct the second region in the chromablock based at least on the second updated offset parameter using theCCLM mode.
 18. The apparatus of claim 13, wherein the chroma blockfurther includes a second region; the luma block includes a first lumaregion and a second luma region that are collocated with the firstregion and the second region, respectively; the first subset of thereconstructed samples includes a plurality of samples in the first lumaregion; and for the second region in the chroma block, the processingcircuitry is configured to: determine a second adjustment parameter usedto adjust the offset parameter in the CCLM mode based on a plurality ofsamples in the second luma region; determine a second updated offsetparameter based at least on the offset parameter and the secondadjustment parameter; and reconstruct the second region in the chromablock based at least on the second updated offset parameter using theCCLM mode.
 19. The apparatus of claim 13, wherein the chroma blockfurther includes a second region; the luma block includes a first lumaregion and a second luma region that are collocated with the firstregion and the second region, respectively; the first subset of thereconstructed samples includes a top-left sample, a top-right sample, abottom-left sample, and a bottom-right sample in the first luma region;and the processing circuitry is configured to: determine the firstadjustment value to be an average of the top-left sample, the top-rightsample, the bottom-left sample, and the bottom-right sample in the firstluma region; and for the second region in the chroma block, determine asecond adjustment parameter used to adjust the offset parameter in theCCLM mode to be an average of a top-left sample, a top-right sample, abottom-left sample, and a bottom-right sample in the second luma region;determine a second updated offset parameter based at least on the secondoffset parameter and the second adjustment parameter; and reconstructthe second region in the chroma block based at least on the secondupdated offset parameter using the CCLM mode.
 20. A non-transitorycomputer-readable storage medium storing instructions which whenexecuted by at least one processor cause the at least one processor toperform: decoding prediction information of a chroma block to bereconstructed in a current picture, the prediction informationindicating that a cross-component linear model (CCLM) mode is applied tothe chroma block; and for a first region in the chroma block,determining a first adjustment value used to modify an offset parameterin the CCLM mode based on a first subset of reconstructed samples in aluma block that is collocated with the chroma block in the currentpicture, the first subset of the reconstructed samples not including oneor more samples in the luma block; updating the offset parameter basedat least on the first adjustment value determining a second adjustmentvalue used to modify a slope parameter in the CCLM mode based on asecond subset of the reconstructed samples in the luma block; updatingthe slope parameter based at least on the second adjustment value; andreconstructing the first region in the chroma block based at least onthe updated offset parameter and the updated slope parameter using theCCLM mode.